Advancements in Crop Analysis through Deep Learning and Explainable AI | Paper Citation Record

Observation 627b78d4-7ceb-4dbe-951d-31c2b3e886f6 · outbound

This paper cites Precision Agriculture Technologies for crop monitoring and management,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Precision Agriculture Technologies for crop monitoring and management,

Reference 1

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Observation ced9b12b-8558-40da-9500-7334bd614f87 · outbound

This paper cites A comprehensive review on smart and sustainable agriculture using IoT technologies,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A comprehensive review on smart and sustainable agriculture using IoT technologies,

Reference 2

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Observation b2c2ed55-5856-4250-b172-d01dfde2d8b3 · outbound

This paper cites A comprehensive review of remote sensing platforms, sensors, and applications in nut crops,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A comprehensive review of remote sensing platforms, sensors, and applications in nut crops,

Reference 3

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Observation 4b3d5113-7c0c-42c7-aa77-9c08b6bc94ff · outbound

This paper cites Remote Sensing from Different Sources for Crop Growth Monitoring in the Area of the Lower Northern Mississippi,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Remote Sensing from Different Sources for Crop Growth Monitoring in the Area of the Lower Northern Mississippi,

Reference 4

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Observation 063f0389-809b-4eaf-ab7c-5d9b358aa739 · outbound

This paper cites Enhancing precision agriculture: A comprehensive review of machine learning and AI vision applications in all-terrain vehicle for farm automation,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Enhancing precision agriculture: A comprehensive review of machine learning and AI vision applications in all-terrain vehicle for farm automation,

Reference 5

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Observation 64582c2f-4bb1-4e5a-a6e3-72e69b3b3a9a · outbound

This paper cites Application of digital technologies for ensuring agricultural productivity,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Application of digital technologies for ensuring agricultural productivity,

Reference 6

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Observation af4b41cc-a616-401a-bbc6-37be6a66fc07 · outbound

This paper cites Sustainable Practices for Enhancing Soil Health and Crop Quality in Modern Agriculture: A Review.,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Sustainable Practices for Enhancing Soil Health and Crop Quality in Modern Agriculture: A Review.,

Reference 7

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Observation 5635fb1a-d60d-4fd5-83ff-efd3a6afde02 · outbound

This paper cites Early diagnosis of rice plant disease using machine learning techniques,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Early diagnosis of rice plant disease using machine learning techniques,

Reference 8

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Observation 26b5bba2-5713-432e-9290-4ab2fa8476e0 · outbound

This paper cites Unravelling the use of artificial intelligence in management of insect pests,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Unravelling the use of artificial intelligence in management of insect pests,

Reference 9

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Observation 2365faae-2cea-4d07-bd67-06c7e86ee280 · outbound

This paper cites Classification of Crops,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Classification of Crops,

Reference 10

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Observation 3182f137-d222-420d-b694-d34cf252d800 · outbound

This paper cites Crops Disease Detection, from Leaves to Field: What We Can Expect from Artificial Intelligence,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crops Disease Detection, from Leaves to Field: What We Can Expect from Artificial Intelligence,

Reference 11

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Observation cd057f95-2ddd-458f-8afc-8eab23aabba9 · outbound

This paper cites A world of 8 billion,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A world of 8 billion,

Reference 12

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Observation f4858f1b-ad4d-48b4-9962-36ae895b8052 · outbound

This paper cites The global population will soon reach 8 billion—then what,.

Advancements in Crop Analysis through Deep Learning and Explainable AI The global population will soon reach 8 billion—then what,

Reference 13

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Observation 22064291-e4ee-4486-a104-17e63440554e · outbound

This paper cites Crowd Scene Analysis using Deep Learning Techniques.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crowd Scene Analysis using Deep Learning Techniques

Reference 14

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Observation 33e50330-2e98-480b-97de-a8aac4ae513e · outbound

This paper cites Crowd Scene Analysis: Crowd Counting using MCNN based on Self-Supervised training with Attention Mechanism,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crowd Scene Analysis: Crowd Counting using MCNN based on Self-Supervised training with Attention Mechanism,

Reference 15

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Observation 4e0a9686-8681-4826-84cd-182572162f6c · outbound

This paper cites Major trends in population growth around the world,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Major trends in population growth around the world,

Reference 16

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Observation e0ac3b00-73a4-493e-ab9f-614945a85279 · outbound

This paper cites What's beneath the future: World population prospects,.

Advancements in Crop Analysis through Deep Learning and Explainable AI What's beneath the future: World population prospects,

Reference 17

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Observation e36afd70-8b15-41bd-8c28-22f4dfaf6729 · outbound

This paper cites Climate change and food security: risks and responses,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Climate change and food security: risks and responses,

Reference 18

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Observation 22875e5a-ee00-4c91-aa12-8024e24924d4 · outbound

This paper cites Advancing sustainability: The impact of emerging technologies in agriculture,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Advancing sustainability: The impact of emerging technologies in agriculture,

Reference 19

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Observation cd431e71-ee3c-4c0c-aa29-530e0d00a629 · outbound

This paper cites IoT-based agriculture management techniques for sustainable farming: A comprehensive review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI IoT-based agriculture management techniques for sustainable farming: A comprehensive review,

Reference 20

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Observation d86f39d2-124f-4768-a8e0-0375b50f1efc · outbound

This paper cites Advanced technologies for precision tree fruit disease management: A review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Advanced technologies for precision tree fruit disease management: A review,

Reference 21

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Observation 84781177-7560-4c01-9546-6148d99170de · outbound

This paper cites Plant disease detection by imaging sensors–parallels and specific demands for precision agriculture and plant phenotyping,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Plant disease detection by imaging sensors–parallels and specific demands for precision agriculture and plant phenotyping,

Reference 22

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Observation be0ef476-4444-4a7a-87ac-22042b2303be · outbound

This paper cites AI-enabled crop health monitoring and nutrient management in smart agriculture,.

Advancements in Crop Analysis through Deep Learning and Explainable AI AI-enabled crop health monitoring and nutrient management in smart agriculture,

Reference 23

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Observation 1a5b305a-9823-461c-82b2-4094045fcb8b · outbound

This paper cites Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides,

Reference 24

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Observation 79a082b4-3d21-4f89-aa46-c30ce11d6daa · outbound

This paper cites Crop Yield Prediction Using Artificial Intelligence and Remote Sensing Methods,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crop Yield Prediction Using Artificial Intelligence and Remote Sensing Methods,

Reference 26

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Observation a8099875-0b12-43a7-a8cb-b455c6eeb0f0 · outbound

This paper cites Tree crop yield estimation and prediction using remote sensing and machine learning: A systematic review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Tree crop yield estimation and prediction using remote sensing and machine learning: A systematic review,

Reference 27

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Observation cbc1a654-9c95-4d28-91f8-f2c5dceda0ad · outbound

This paper cites Artificial intelligence techniques in crop yield estimation based on Sentinel-2 data: A comprehensive survey,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Artificial intelligence techniques in crop yield estimation based on Sentinel-2 data: A comprehensive survey,

Reference 28

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Observation 47bca004-0967-4ff8-9660-135c5df09175 · outbound

This paper cites Crop yield prediction using machine learning: A systematic literature review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crop yield prediction using machine learning: A systematic literature review,

Reference 29

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Observation 4f72cccc-5a0f-4b24-a555-485447bca1d4 · outbound

This paper cites Crop price prediction using supervised machine learning algorithms,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crop price prediction using supervised machine learning algorithms,

Reference 30

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Observation b24b63e0-62b8-44c9-90d7-2884cd701302 · outbound

This paper cites Crop price prediction system using machine learning algorithms,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crop price prediction system using machine learning algorithms,

Reference 31

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Observation 96509829-4e5a-48fe-b017-aad33bab1f33 · outbound

This paper cites An intelligent crop price prediction using suitable machine learning algorithm,.

Advancements in Crop Analysis through Deep Learning and Explainable AI An intelligent crop price prediction using suitable machine learning algorithm,

Reference 32

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Observation 1e8bf7da-9efe-49ad-9b5f-eb1593e68a59 · outbound

This paper cites Farm\_{e}{r}{a}: Precision farming with GIS, AI pest management, smart irrigation, data analytics, and optimized crop planning,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Farm\_{e}{r}{a}: Precision farming with GIS, AI pest management, smart irrigation, data analytics, and optimized crop planning,

Reference 33

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Observation c7554e7a-b876-4b19-b23e-b5729f688b82 · outbound

This paper cites Advanced technologies and artificial intelligence in agriculture,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Advanced technologies and artificial intelligence in agriculture,

Reference 34

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Observation 7910c744-ffd4-4ed6-87b7-0de350dfa403 · outbound

This paper cites Crop classification method based on optimal feature selection and hybrid CNN-RF networks for multi-temporal remote sensing imagery,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Crop classification method based on optimal feature selection and hybrid CNN-RF networks for multi-temporal remote sensing imagery,

Reference 35

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Observation 6632c8da-57cb-48d8-995c-ff50e74939f7 · outbound

This paper cites Classification of white rice grain quality using ANN: a review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Classification of white rice grain quality using ANN: a review,

Reference 36

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Observation c3885915-28bc-4588-9617-5dd1a2ab3404 · outbound

This paper cites Contrastive analysis of rice grain classification techniques: multi-class support vector machine vs artificial neural network,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Contrastive analysis of rice grain classification techniques: multi-class support vector machine vs artificial neural network,

Reference 37

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Observation 1702636e-e56e-49fd-bc07-c788518b7207 · outbound

This paper cites Smart disease detection system for citrus fruits using deep learning with edge computing,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Smart disease detection system for citrus fruits using deep learning with edge computing,

Reference 38

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Observation d8e125f5-0966-45f6-90b9-a8b17a24c4cb · outbound

This paper cites Enhancing rice leaf disease classification: a customized convolutional neural network approach,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Enhancing rice leaf disease classification: a customized convolutional neural network approach,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.583866Z

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Observation 54b5a85b-1b51-4a7d-ba45-34af81b4a32e · outbound

This paper cites Enhancing rice crop management: Disease classification using convolutional neural networks and mobile application integration,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Enhancing rice crop management: Disease classification using convolutional neural networks and mobile application integration,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.569468Z

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Observation 65948bab-18e7-41ff-b1f0-455eba82b898 · outbound

This paper cites Rice Disease Recognition using Transfer Learning Xception Convolutional Neural Network,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice Disease Recognition using Transfer Learning Xception Convolutional Neural Network,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.554775Z

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Observation d2d530a7-641d-4d9c-a82a-a2c10757a1a9 · outbound

This paper cites A disease index for efficiently detecting wheat fusarium head blight using sentinel-2 multispectral imagery,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A disease index for efficiently detecting wheat fusarium head blight using sentinel-2 multispectral imagery,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.540464Z

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Observation f1bf33d2-4235-4b65-a648-dc9f4615ad76 · outbound

This paper cites Close range spectral imaging for disease detection in plants using autonomous platforms: a review on recent studies,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Close range spectral imaging for disease detection in plants using autonomous platforms: a review on recent studies,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.521556Z

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Observation 2cba4b81-f3a2-4b2b-9e13-cef66720e5c4 · outbound

This paper cites Comparative Study of Various Optimizers and Transfer Learning Methods of Rice Leaf Disease Detection Using CNN,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Comparative Study of Various Optimizers and Transfer Learning Methods of Rice Leaf Disease Detection Using CNN,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.506943Z

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This paper cites Transfer learning using vgg-16 with deep convolutional neural network for classifying images,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Transfer learning using vgg-16 with deep convolutional neural network for classifying images,

Reference 45

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Observation 0991c63e-ba9c-49bc-8cd4-5173977e46a6 · outbound

This paper cites Rethinking the inception architecture for computer vision,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rethinking the inception architecture for computer vision,

Reference 46

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This paper cites Searching for mobilenetv3,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Searching for mobilenetv3,

Reference 47

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This paper cites " Why should i trust you?.

Advancements in Crop Analysis through Deep Learning and Explainable AI " Why should i trust you?

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.449218Z

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Observation 3d4b30a2-e504-4bcc-bbd1-14d9b45a1b63 · outbound

This paper cites A study of LIME and SHAP model explainers for autonomous disease predictions,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A study of LIME and SHAP model explainers for autonomous disease predictions,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.434584Z

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This paper cites A perspective on explainable artificial intelligence methods: SHAP and LIME,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A perspective on explainable artificial intelligence methods: SHAP and LIME,

Reference 50

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This paper cites A unified approach to interpreting model predictions,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A unified approach to interpreting model predictions,

Reference 51

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This paper cites Strategic Customer Segmentation: Harnessing Machine Learning For Retaining Satisfied Customers,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Strategic Customer Segmentation: Harnessing Machine Learning For Retaining Satisfied Customers,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.390616Z

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Observation 76a3d7b8-c1bc-4cf6-b409-64bc9cf8c82b · outbound

This paper cites Advanced artificial intelligence techniques for real-time predictive maintenance in industrial IoT systems: a comprehensive analysis and framework,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Advanced artificial intelligence techniques for real-time predictive maintenance in industrial IoT systems: a comprehensive analysis and framework,

Reference 53

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Observation 17bf375c-5fbb-4033-9b6c-0a15d5f62fab · outbound

This paper cites A comprehensive review on breast cancer detection, classification and segmentation using deep learning,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A comprehensive review on breast cancer detection, classification and segmentation using deep learning,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.362170Z

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This paper cites A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.347786Z

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Observation 0f405c9e-2089-46e5-90d2-10fa1d1347c8 · outbound

This paper cites Deep learning-based approaches for robust classification of cervical cancer,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Deep learning-based approaches for robust classification of cervical cancer,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.333237Z

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Observation 4869ab97-74c5-4f73-93d2-7d1ae9c66c2a · outbound

This paper cites Convolution neural network for breast cancer detection and classification using deep learning,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Convolution neural network for breast cancer detection and classification using deep learning,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.318098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3ee0999f-39b2-481a-b31c-276d3d07f586 · outbound

This paper cites Machine learning-based patient classification system for adults with stroke: a systematic review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Machine learning-based patient classification system for adults with stroke: a systematic review,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.303738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation be870d90-21ce-4e1c-9762-0b8e6f0a2215 · outbound

This paper cites Development of Pneumonia Patient Classification Model Using Fair Federated Learning,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Development of Pneumonia Patient Classification Model Using Fair Federated Learning,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.289221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 19d673b4-0656-4c01-8bd2-85b6f3fcde09 · outbound

This paper cites Classification of rice varieties with deep learning methods,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Classification of rice varieties with deep learning methods,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.275038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4c6a412d-cc2f-43a6-9bd8-3cd25e167461 · outbound

This paper cites A comprehensive survey on weed and crop classification using machine learning and deep learning,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A comprehensive survey on weed and crop classification using machine learning and deep learning,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.260834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b6a6f3b1-36e1-4452-b896-8b94b6e79338 · outbound

This paper cites Machine learning approach for the classification of wheat grains,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Machine learning approach for the classification of wheat grains,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.246279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69395e19-ff63-46f5-a78f-24ec958211e3 · outbound

This paper cites Enhancing Sustainable Rice Grain Quality Analysis with Efficient SVM Optimization Using Genetic Algorithm,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Enhancing Sustainable Rice Grain Quality Analysis with Efficient SVM Optimization Using Genetic Algorithm,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.230768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1fe8bbc6-07e5-4fcc-b3eb-bb7eddc56a0f · outbound

This paper cites Detection and classification of tomato crop disease using convolutional neural network,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Detection and classification of tomato crop disease using convolutional neural network,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.216245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6e77f707-f97a-4004-ade2-61d226d2d157 · outbound

This paper cites Rice (Oryza Sativa) Grading classification using Hybrid Model Deep Convolutional Neural Networks-Support Vector Machine Classifier,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice (Oryza Sativa) Grading classification using Hybrid Model Deep Convolutional Neural Networks-Support Vector Machine Classifier,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.202369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ef8c2eb1-9798-41f7-a5ae-925f41205c88 · outbound

This paper cites Rice Grain Classification for Agricultural Products Marketing-A Deep Learning Approach,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice Grain Classification for Agricultural Products Marketing-A Deep Learning Approach,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.188123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6e53a339-3578-4c24-b739-8bdf616e182c · outbound

This paper cites A generic approach for wheat disease classification and verification using expert opinion for knowledge-based decisions,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A generic approach for wheat disease classification and verification using expert opinion for knowledge-based decisions,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.174251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 444875dc-0c88-440d-abaf-c794aa959911 · outbound

This paper cites Rice varieties classification using machine learning algorithms,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice varieties classification using machine learning algorithms,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.158933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d54ab816-2dab-4053-8e9d-69662e115bcd · outbound

This paper cites Seasonal crops disease prediction and classification using deep convolutional encoder network,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Seasonal crops disease prediction and classification using deep convolutional encoder network,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.143674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c520189f-5e81-44e6-9bd3-3cbae750ef99 · outbound

This paper cites Rice leaf disease detection using machine learning techniques,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice leaf disease detection using machine learning techniques,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.126280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ac3274ca-9109-4344-be05-f95d818a9202 · outbound

This paper cites Automated recognition of rice grain diseases using deep learning,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Automated recognition of rice grain diseases using deep learning,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.110309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 655539c2-5d94-41da-8f00-3ce9a9b2776c · outbound

This paper cites Exploring classification of rice leaf diseases using machine learning and deep learning,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Exploring classification of rice leaf diseases using machine learning and deep learning,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.093442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a56ae173-51c0-4c89-80a0-7abf39f81a91 · outbound

This paper cites Automated wheat Disease detection using Deep Learning: an object detection and Classification approach,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Automated wheat Disease detection using Deep Learning: an object detection and Classification approach,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.077239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5a293b05-3ee2-4918-ab6d-66301e1c7ade · outbound

This paper cites Smart paddy crop disease identification and management using deep convolution neural network and SVM classifier,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Smart paddy crop disease identification and management using deep convolution neural network and SVM classifier,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.061587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1afa8a87-105c-4d40-bc96-fab99ad86637 · outbound

This paper cites Rice blast disease recognition using a deep convolutional neural network,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice blast disease recognition using a deep convolutional neural network,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.046661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9da242d8-5ea5-433f-aa10-6452f2b44cfd · outbound

This paper cites Rice plant disease detection using image processing and probabilistic neural network,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice plant disease detection using image processing and probabilistic neural network,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.031629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cfbd2261-9966-44fe-83f0-a1d7af7ec468 · outbound

This paper cites Deep feature based rice leaf disease identification using support vector machine,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Deep feature based rice leaf disease identification using support vector machine,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.016213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f4a308aa-4633-464d-8e1d-bc8bb62bc98b · outbound

This paper cites A deep learning approach for inter-patient classification of premature ventricular contraction from electrocardiogram,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A deep learning approach for inter-patient classification of premature ventricular contraction from electrocardiogram,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:02.001208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 84fdd84e-17e0-4607-bd35-8978ca47db8c · outbound

This paper cites Application of AI techniques and robotics in agriculture: A review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Application of AI techniques and robotics in agriculture: A review,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.985961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4a615b26-d0f4-4170-965d-683971e53774 · outbound

This paper cites Agricultural land systems importance for supporting food security and sustainable development goals: A systematic review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Agricultural land systems importance for supporting food security and sustainable development goals: A systematic review,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.971207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9b96763f-5d5b-4c4e-960d-2d0621a105f1 · outbound

This paper cites Rice Varieties Classification Using Neural Network and Transfer Learning with MobileNetV2,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice Varieties Classification Using Neural Network and Transfer Learning with MobileNetV2,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.955821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b1ebfac8-e1fe-4375-a828-435a43e80276 · outbound

This paper cites Rice leaves disease detection and classification using transfer learning technique,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Rice leaves disease detection and classification using transfer learning technique,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.940807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 560890d5-4814-4eb8-9b6f-847f28eb2024 · outbound

This paper cites an unresolved cited work.

Advancements in Crop Analysis through Deep Learning and Explainable AI Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:18:01.924544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5ad2d4be-108c-46d4-b0dc-4f3dbb8821f1 · outbound

This paper cites CNN Architectures: Alex Net, Le Net, VGG, Google Net, Res Net,.

Advancements in Crop Analysis through Deep Learning and Explainable AI CNN Architectures: Alex Net, Le Net, VGG, Google Net, Res Net,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.908206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation af958d39-e02b-4176-840e-75039407ad82 · outbound

This paper cites Robots in agriculture: prospects, impacts, ethics, and policy,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Robots in agriculture: prospects, impacts, ethics, and policy,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.891677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7eccf363-e5ca-49d5-afd4-bfff6dd82cd4 · outbound

This paper cites Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.876343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6c28c47c-70ba-4508-b15c-c98479c96fd7 · outbound

This paper cites Sustainable farming practices and soil health: A pathway to achieving SDGs and future prospects,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Sustainable farming practices and soil health: A pathway to achieving SDGs and future prospects,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.860842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7a697558-afc2-459c-85a6-e49d0e6eb904 · outbound

This paper cites Applications of remote sensing in agriculture-A Review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Applications of remote sensing in agriculture-A Review,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.845245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d183ac2-58b7-4042-a0c4-ac645196ad08 · outbound

This paper cites Deep learning in neural networks: An overview,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Deep learning in neural networks: An overview,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.829196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8423de20-b2ac-4bd7-86e1-47d9a785ef13 · outbound

This paper cites Path planning aware of robot’s center of mass for steep slope vineyards,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Path planning aware of robot’s center of mass for steep slope vineyards,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.814060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b2886135-7373-4cfb-9305-eb9bd4a1a763 · outbound

This paper cites A cascade network for the classification of rice grain based on single rice kernel,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A cascade network for the classification of rice grain based on single rice kernel,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.799077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c558d806-e2d4-460f-a2f8-f32bb9fa17d2 · outbound

This paper cites Optimizing Crop Yield Prediction in Precision Agriculture with Hyperspectral Imaging-Unmixing and Deep Learning.,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Optimizing Crop Yield Prediction in Precision Agriculture with Hyperspectral Imaging-Unmixing and Deep Learning.,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.782924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0a22e8dd-c00c-46c3-bbce-5136f4aa8cc6 · outbound

This paper cites Machine vision approach for classification of rice varieties using texture features,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Machine vision approach for classification of rice varieties using texture features,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.767481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f492e7b4-9395-4331-a311-7532feb84c0c · outbound

This paper cites DeepRiceTransfer: Exploiting CNN Transfer Learning for Effective Rice Variety Classification,.

Advancements in Crop Analysis through Deep Learning and Explainable AI DeepRiceTransfer: Exploiting CNN Transfer Learning for Effective Rice Variety Classification,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.749348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e64e5178-81da-49a8-bcb3-c12a5877bd65 · outbound

This paper cites A model for smart agriculture using IoT,.

Advancements in Crop Analysis through Deep Learning and Explainable AI A model for smart agriculture using IoT,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.732549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a5618330-a8b6-4409-ae3b-a811204581dd · outbound

This paper cites Deep learning-based classification of fruit diseases: An application for precision agriculture,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Deep learning-based classification of fruit diseases: An application for precision agriculture,

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.717213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 168112b6-e74f-4a5d-a1c8-22da46fceb4d · outbound

This paper cites Remote sensing and AI-based monitoring of legume crop health and growth,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Remote sensing and AI-based monitoring of legume crop health and growth,

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-05T16:18:01.376740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bc511c6-8c52-4f21-9889-448912fec66d · outbound

This paper cites Precision agriculture for crop and livestock farming—Brief review,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Precision agriculture for crop and livestock farming—Brief review,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.702748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 72803bb6-e215-4b0b-89ed-a0b79ba703de · outbound

This paper cites An overview of cooperative robotics in agriculture,.

Advancements in Crop Analysis through Deep Learning and Explainable AI An overview of cooperative robotics in agriculture,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.688243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ea7e53c6-674f-437a-a76e-938db1e0c1c9 · outbound

This paper cites Kujawa and G.

Advancements in Crop Analysis through Deep Learning and Explainable AI Kujawa and G

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.672727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 74ff682f-6b86-4f5e-afa3-e8fe0ac2a447 · outbound

This paper cites Remote sensing in agriculture— accomplishments, limitations, and opportunities,.

Advancements in Crop Analysis through Deep Learning and Explainable AI Remote sensing in agriculture— accomplishments, limitations, and opportunities,

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:18:01.657061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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