ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation | Paper Citation Record

Observation 5d829ecb-dabe-4a54-9d75-85557dddc099 · outbound

This paper cites STransFuse: Fusing swin transformer and convolutional neural network for remote sensing image semantic segmentation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation STransFuse: Fusing swin transformer and convolutional neural network for remote sensing image semantic segmentation,

Reference 1

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Observation 753f186f-1bc5-445b-b8e8-0e5cf0057c43 · outbound

This paper cites Predictive maintenance on the machining process and machine tool,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Predictive maintenance on the machining process and machine tool,

Reference 2

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Observation f13070af-15df-4ee2-93b9-c21515b543fa · outbound

This paper cites A review of recent advances in surface defect detection using texture analysis techniques,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation A review of recent advances in surface defect detection using texture analysis techniques,

Reference 3

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Observation b6b5254a-5bd9-493b-a831-99a80d9cab3e · outbound

This paper cites Automated visual inspection in the semi- conductor industry: A survey,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Automated visual inspection in the semi- conductor industry: A survey,

Reference 4

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Observation dc34f458-f49b-4191-963c-7ab4b013a30d · outbound

This paper cites Automated inspection of surface defects using machine vision,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Automated inspection of surface defects using machine vision,

Reference 5

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Observation 1dfd8840-c2b4-413d-ac88-b2c54c460a2c · outbound

This paper cites Review of wafer surface defect detection methods,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Review of wafer surface defect detection methods,

Reference 6

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Observation cf93436a-e343-4c9a-922d-4ea7a6891e96 · outbound

This paper cites Testing open defects in memristor-based memories,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Testing open defects in memristor-based memories,

Reference 7

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Observation 8366fa4e-54eb-4b2e-a029-820a382382d3 · outbound

This paper cites Warpage, stresses and koz of 3d tsv dram package during manufacturing processes,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Warpage, stresses and koz of 3d tsv dram package during manufacturing processes,

Reference 8

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Observation 538ec2f5-663b-491e-91aa-05cfc2be155d · outbound

This paper cites Inspection and classification of semiconductor wafer surface defects using CNN deep learning networks,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Inspection and classification of semiconductor wafer surface defects using CNN deep learning networks,

Reference 9

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Observation f3d9e05a-5a69-4713-b10c-32d4d260a978 · outbound

This paper cites Tlu-net: a deep learning approach for automatic steel surface defect detection,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Tlu-net: a deep learning approach for automatic steel surface defect detection,

Reference 10

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Observation 8226680f-0b46-4a09-9a32-4290fdf76e92 · outbound

This paper cites Artificial intelligence in semiconductor manufacturing,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Artificial intelligence in semiconductor manufacturing,

Reference 11

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Observation e0deb26c-b02f-47ed-b90f-819c77516fcf · outbound

This paper cites Integrated circuit packaging defect analysis and deep learning detection method,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Integrated circuit packaging defect analysis and deep learning detection method,

Reference 12

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Observation 80073d30-ecde-44aa-8ce2-490e4cbcf100 · outbound

This paper cites Periodic surface defect detection in steel plates based on deep learning,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Periodic surface defect detection in steel plates based on deep learning,

Reference 13

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Observation a0f59e71-ac4f-4c00-b830-04238af97fd4 · outbound

This paper cites Deep learning for semiconductor defect classification,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Deep learning for semiconductor defect classification,

Reference 14

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Observation 36fdacc4-977a-4b27-8b94-0a56cf5e9d60 · outbound

This paper cites Deep neural network– based detection and verification of microelectronic images,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Deep neural network– based detection and verification of microelectronic images,

Reference 15

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Observation a38d5e53-900c-489f-83e0-7c4265106584 · outbound

This paper cites Smd led chips defect detection using a yolov3-dense model,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Smd led chips defect detection using a yolov3-dense model,

Reference 16

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Observation 2cae4443-7db9-4dd5-a689-bb50077797cd · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 17

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Observation e1cf8116-3c2c-41b3-9ab5-a16c4d7cb96c · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 18

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Observation 2b496949-e394-4fcc-a841-cd8c69f69fb4 · outbound

This paper cites Dilated Neighborhood Attention Transformer.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Dilated Neighborhood Attention Transformer

Reference 19

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Observation 6962b623-62b4-42a1-98e4-ea98ae842927 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 20

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Observation f7f2d6ba-15bc-41d7-a209-36d70ca08625 · outbound

This paper cites Cracks segmentation of engineering structures in complex backgrounds using a concatenation of transformer and cnn models driven by scene understanding information,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Cracks segmentation of engineering structures in complex backgrounds using a concatenation of transformer and cnn models driven by scene understanding information,

Reference 21

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Observation 5a12f3a8-7eb3-4b00-8cb2-06bd49272516 · outbound

This paper cites Scsnet: a novel transformer-cnn fusion architecture for enhanced segmentation and classification on high- resolution semiconductor micro-scale defects,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Scsnet: a novel transformer-cnn fusion architecture for enhanced segmentation and classification on high- resolution semiconductor micro-scale defects,

Reference 22

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Observation beb0b8a4-86af-43a8-9e2e-50d230f54448 · outbound

This paper cites Generalized complete local binary pattern for robust scratch detection,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Generalized complete local binary pattern for robust scratch detection,

Reference 23

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Observation 7f39c9c5-5766-4443-8e51-96ff6f1083e7 · outbound

This paper cites Hypergraph video pedestrian re-identification based on posture structure relationship and action constraints,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Hypergraph video pedestrian re-identification based on posture structure relationship and action constraints,

Reference 24

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Observation 7f1c228f-9177-4195-b062-eec7cb868b31 · outbound

This paper cites Research on the optimizing process of the basic image processing algorithms,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Research on the optimizing process of the basic image processing algorithms,

Reference 25

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Observation f3b627db-708d-464b-a260-57d4e9f3ce9f · outbound

This paper cites Machine learning-based image processing for on-line defect recognition in addi- tive manufacturing,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Machine learning-based image processing for on-line defect recognition in addi- tive manufacturing,

Reference 26

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Observation 20904617-f2cf-4d9e-afd9-181ceaf307fc · outbound

This paper cites Advances in biomedical signal and im- age processing–a systematic review,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Advances in biomedical signal and im- age processing–a systematic review,

Reference 27

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Observation e49b07c0-3fc3-4e6b-a186-3c18f4d43251 · outbound

This paper cites A wavelet-based approach in detecting visual defects on semiconductor wafer dies,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation A wavelet-based approach in detecting visual defects on semiconductor wafer dies,

Reference 28

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Observation 0ffa0cff-3a72-4cb8-8d88-cf56a8728e0f · outbound

This paper cites Short-time discrete wavelet transform for wafer microc- rack detection,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Short-time discrete wavelet transform for wafer microc- rack detection,

Reference 29

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Observation 5834aadc-0863-4950-8587-be839f95283c · outbound

This paper cites Polycrystalline silicon wafer defect segmentation based on deep convolutional neural networks,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Polycrystalline silicon wafer defect segmentation based on deep convolutional neural networks,

Reference 30

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Observation df03a85c-6fc6-423d-bcc9-c285a556a72c · outbound

This paper cites Detection of spatial defect patterns generated in semiconductor fabrication processes,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Detection of spatial defect patterns generated in semiconductor fabrication processes,

Reference 31

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Observation 9ea7cd10-f37c-4852-9b8a-de72dd562f00 · outbound

This paper cites Decision tree ensemble- based wafer map failure pattern recognition based on radon transform- based features,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Decision tree ensemble- based wafer map failure pattern recognition based on radon transform- based features,

Reference 32

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Observation a18a595d-f2a9-4df8-a150-1f5f35297195 · outbound

This paper cites Non-Destructive Detection of Sub-Micron Imperceptible Scratches On Laser Chips Based On Consistent Texture Entropy Recursive Optimization Semi-Supervised Network.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Non-Destructive Detection of Sub-Micron Imperceptible Scratches On Laser Chips Based On Consistent Texture Entropy Recursive Optimization Semi-Supervised Network

Reference 33

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Observation 5f970f6c-22e3-4473-8904-794faad0f4c6 · outbound

This paper cites Inspection and classification of semiconductor wafer surface defects using cnn deep learning networks,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Inspection and classification of semiconductor wafer surface defects using cnn deep learning networks,

Reference 34

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Observation e02d68bf-d3b1-41fd-861a-487d5a09f39d · outbound

This paper cites A novel method based on deep convolutional neural networks for wafer semiconductor surface defect inspection,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation A novel method based on deep convolutional neural networks for wafer semiconductor surface defect inspection,

Reference 35

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Observation 33945ea6-b64e-4532-8473-ab22d7946e7a · outbound

This paper cites Deep learning-based detection, classification, and localization of defects in semiconductor processes,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Deep learning-based detection, classification, and localization of defects in semiconductor processes,

Reference 36

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Observation 55427d91-bf58-411f-9b4b-2c55cb387924 · outbound

This paper cites Machine learning-based detection method for wafer test induced defects,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Machine learning-based detection method for wafer test induced defects,

Reference 37

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Observation 508df2b1-c80f-4f7e-b285-d51a34b950aa · outbound

This paper cites Deformable convolutional networks for efficient mixed-type wafer defect pattern recognition,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Deformable convolutional networks for efficient mixed-type wafer defect pattern recognition,

Reference 38

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Observation e8a7d0f9-aadf-409c-a703-48cfdb5f85ed · outbound

This paper cites Classification of mixed-type defect patterns in wafer bin maps using convolutional neural networks,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Classification of mixed-type defect patterns in wafer bin maps using convolutional neural networks,

Reference 39

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Observation dd32dfdd-ac59-4e8e-b8c9-f57089120fc3 · outbound

This paper cites A wafer scratch detection method for correction and completing results of semantic segmentation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation A wafer scratch detection method for correction and completing results of semantic segmentation,

Reference 40

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Observation ee8b9a31-d3eb-4e62-b7db-96f1637f918a · outbound

This paper cites RA-UNet: A new deep learning segmentation method for semiconductor wafer defect analysis on fine-grained scanning electron microscope (sem) images,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation RA-UNet: A new deep learning segmentation method for semiconductor wafer defect analysis on fine-grained scanning electron microscope (sem) images,

Reference 41

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Observation 4abe2a57-537c-4f74-ac54-270713857d1d · outbound

This paper cites Global context enhanced resolution networks for sapphire scratch detection and classi- fication,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Global context enhanced resolution networks for sapphire scratch detection and classi- fication,

Reference 42

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Observation b4fe45e5-aae4-4b49-a6cf-e09cc402c035 · outbound

This paper cites Deepsem-net: Enhancing sem defect analysis in semiconductor manufacturing with a dual-branch cnn- transformer architecture,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Deepsem-net: Enhancing sem defect analysis in semiconductor manufacturing with a dual-branch cnn- transformer architecture,

Reference 43

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This paper cites Fully convolutional networks for semantic segmentation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Fully convolutional networks for semantic segmentation,

Reference 44

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Observation 15d121f9-df6f-4ccb-a9df-9f0b21f267b8 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation U-net: Convolutional networks for biomedical image segmentation,

Reference 45

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Observation ef6e4c1b-d8b4-4788-8ff8-9a9bebbaed9a · outbound

This paper cites Unified perceptual parsing for scene understanding,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Unified perceptual parsing for scene understanding,

Reference 46

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Observation b9f16dcf-76d1-4547-b54b-a651cbba48ec · outbound

This paper cites Polycrystalline silicon wafer scratch segmentation based on deep convolutional autoencoder,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Polycrystalline silicon wafer scratch segmentation based on deep convolutional autoencoder,

Reference 47

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This paper cites Xcnet: Enhancing defect detection in sensor boards through data quality analysis and convolutional neural networks,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Xcnet: Enhancing defect detection in sensor boards through data quality analysis and convolutional neural networks,

Reference 48

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This paper cites Feature pyramid networks for object detection,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Feature pyramid networks for object detection,

Reference 49

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Observation b79a6da0-2550-4822-904f-c6be81ab4dd5 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 50

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This paper cites Wtpose: Waterfall transformer for multi-person pose estimation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Wtpose: Waterfall transformer for multi-person pose estimation,

Reference 51

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This paper cites Deep high- resolution representation learning for visual recognition,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Deep high- resolution representation learning for visual recognition,

Reference 52

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Observation e3c403ba-fb8a-4dc0-ad66-3ee45f56f69e · outbound

This paper cites Large- scale road network traffic congestion prediction based on recurrent high- resolution network,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Large- scale road network traffic congestion prediction based on recurrent high- resolution network,

Reference 53

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Observation 089f8854-c1f9-4acf-ad45-c193f2a7cec4 · outbound

This paper cites Yoloseg with applications to wafer die particle defect segmentation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Yoloseg with applications to wafer die particle defect segmentation,

Reference 54

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This paper cites Deep residual learning for image recognition,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Deep residual learning for image recognition,

Reference 55

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Observation 033806e1-efa1-4f42-83fa-0df3b7af26c0 · outbound

This paper cites Surface defect detection in industrial appli- cations using reference-based deep learning,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Surface defect detection in industrial appli- cations using reference-based deep learning,

Reference 56

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This paper cites Boundary iou: Improving object-centric image segmentation evaluation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Boundary iou: Improving object-centric image segmentation evaluation,

Reference 57

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Observation b27e5b36-ad5a-4497-ab94-25f01cb49d07 · outbound

This paper cites A modified hausdorff distance for object matching,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation A modified hausdorff distance for object matching,

Reference 58

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This paper cites Segment anything,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Segment anything,

Reference 59

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This paper cites Clipsam: Clip and sam collaboration for zero-shot anomaly segmentation,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Clipsam: Clip and sam collaboration for zero-shot anomaly segmentation,

Reference 60

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Observation ffa0c436-4ceb-4b5e-a159-070b9a52c77e · outbound

This paper cites Better image segmenta- tion with classification: Guiding zero-shot models using class activation maps,.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Better image segmenta- tion with classification: Guiding zero-shot models using class activation maps,

Reference 61

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Observation c4bd847e-0cb1-4546-a284-9fc6abe60a27 · outbound

This paper cites an unresolved cited work.

ScratNet: A Swin-Based Multi-Scale Dilated Network with Precision Refinement for Semiconductor Scratch Segmentation Unresolved cited work

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