Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach | Paper Citation Record

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This paper cites Pcb-vision: A multiscene rgb-hyperspectral benchmark dataset of printed circuit boards.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Pcb-vision: A multiscene rgb-hyperspectral benchmark dataset of printed circuit boards

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This paper cites Electrolyzers-hsi: Close-range multi-scene hyperspectral imaging benchmark dataset.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Electrolyzers-hsi: Close-range multi-scene hyperspectral imaging benchmark dataset

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This paper cites Towards greater circularity in the hydrogen technology value chain.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Towards greater circularity in the hydrogen technology value chain

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Wastegan: Data augmentation for robotic waste sorting through generative adversarial networks

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This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

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This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 6

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This paper cites Domestic waste detection and grasping points for robotic picking up.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Domestic waste detection and grasping points for robotic picking up

Reference 7

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This paper cites End-of-life of fuel cell and hydrogen products: A state of the art.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach End-of-life of fuel cell and hydrogen products: A state of the art

Reference 8

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This paper cites Vision based process monitoring in wire arc additive manufacturing (waam).

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Vision based process monitoring in wire arc additive manufacturing (waam)

Reference 9

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This paper cites Dual attention network for scene segmentation.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Dual attention network for scene segmentation

Reference 10

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This paper cites Cafnet: Cross-modal adaptive fusion network with attention and gated weighting for rgb-t semantic segmentation.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Cafnet: Cross-modal adaptive fusion network with attention and gated weighting for rgb-t semantic segmentation

Reference 11

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This paper cites u hmstedt, Gunther Notni, and Andreas T \.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach u hmstedt, Gunther Notni, and Andreas T \

Reference 12

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This paper cites Coordinate attention for efficient mobile network design.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Coordinate attention for efficient mobile network design

Reference 13

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This paper cites Data-centric approach for instance segmentation in optical waste sorting.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Data-centric approach for instance segmentation in optical waste sorting

Reference 14

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This paper cites A survey of hydrogen electrolyzer technologies for canada’s clean energy transition.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach A survey of hydrogen electrolyzer technologies for canada’s clean energy transition

Reference 15

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Observation 7fc28db3-216c-4789-9ffd-22d8a2ca2782 · outbound

This paper cites Life-cycle analysis of hydrogen production from water electrolyzers.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Life-cycle analysis of hydrogen production from water electrolyzers

Reference 16

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This paper cites An ensemble learning approach towards waste segmentation in cluttered environment.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach An ensemble learning approach towards waste segmentation in cluttered environment

Reference 17

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This paper cites RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation

Reference 18

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This paper cites Smfps: A semi-supervised multi-modal fusion method for rgbd particle segmentation of industrial materials.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Smfps: A semi-supervised multi-modal fusion method for rgbd particle segmentation of industrial materials

Reference 19

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This paper cites Global-aware interaction network for rgb-d salient object detection.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Global-aware interaction network for rgb-d salient object detection

Reference 20

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This paper cites u nner, Dominik Goes, Jeraldine Lastam, Shine-Od Mongoljiibuu, Stephan Sarner, Alexander Specht, J \.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach u nner, Dominik Goes, Jeraldine Lastam, Shine-Od Mongoljiibuu, Stephan Sarner, Alexander Specht, J \

Reference 21

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This paper cites Strategies for life cycle impact reduction of green hydrogen production--influence of electrolyser value chain design.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Strategies for life cycle impact reduction of green hydrogen production--influence of electrolyser value chain design

Reference 22

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This paper cites Multi-modal sorting in plastic and wood waste streams.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Multi-modal sorting in plastic and wood waste streams

Reference 23

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This paper cites Robotic waste sorting technology: Toward a vision-based categorization system for the industrial robotic separation of recyclable waste.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Robotic waste sorting technology: Toward a vision-based categorization system for the industrial robotic separation of recyclable waste

Reference 24

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Deeply-supervised nets

Reference 25

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions

Reference 26

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Cascaded hierarchical atrous spatial pyramid pooling module for semantic segmentation

Reference 27

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This paper cites Life-cycle assessment of hydrogen technologies with the focus on eu critical raw materials and end-of-life strategies.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Life-cycle assessment of hydrogen technologies with the focus on eu critical raw materials and end-of-life strategies

Reference 28

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Using computer vision to recognize composition of construction waste mixtures: A semantic segmentation approach

Reference 29

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Loss odyssey in medical image segmentation

Reference 30

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Hyperspectral band selection for multispectral image classification with convolutional networks

Reference 31

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Hyperspectral Dataset and Deep Learning methods for Waste from Electric and Electronic Equipment Identification (WEEE)

Reference 32

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This paper cites Wasteinnet: Deep learning model for real-time identification of various types of waste.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Wasteinnet: Deep learning model for real-time identification of various types of waste

Reference 33

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach U-net: Convolutional networks for biomedical image segmentation

Reference 34

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Tversky loss function for image segmentation using 3d fully convolutional deep networks

Reference 35

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 36

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Automated electro-construction waste sorting: Computer vision for part-level segmentation

Reference 37

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Expansion-squeeze-excitation fusion network for elderly activity recognition

Reference 38

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Image analysis and quantification on solid oxide fuel cell anode through inspired cnn based u-net architecture

Reference 39

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This paper cites Deep learning for full-feature x-ray microcomputed tomography segmentation of proton electron membrane fuel cells.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Deep learning for full-feature x-ray microcomputed tomography segmentation of proton electron membrane fuel cells

Reference 40

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Electrolyzer and fuel cell recycling for a circular hydrogen economy

Reference 41

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This paper cites End of life of fuel cells and hydrogen products: From technologies to strategies.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach End of life of fuel cells and hydrogen products: From technologies to strategies

Reference 42

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Image segmentation network based on enhanced dual encoder

Reference 43

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Eca-net: Efficient channel attention for deep convolutional neural networks

Reference 44

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Cross-modal retrieval: a systematic review of methods and future directions

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning

Reference 46

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Complementary information-guided interactive fusion network for hsi and lidar data joint classification

Reference 47

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Unified focal loss: Generalising dice and cross entropy-based losses to handle class imbalanced medical image segmentation

Reference 48

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Leveraging computer vision towards high-efficiency autonomous industrial facilities

Reference 49

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This paper cites Hierarchical waste detection with weakly supervised segmentation in images from recycling plants.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Hierarchical waste detection with weakly supervised segmentation in images from recycling plants

Reference 50

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Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Generative ai in industrial machine vision: a review

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Observation fa891f92-4bf5-48eb-b0f8-0ebdb6b70356 · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmentation.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Unet++: A nested u-net architecture for medical image segmentation

Reference 52

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This paper cites Hyperspectral image denoising and anomaly detection based on low-rank and sparse representations.

Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach Hyperspectral image denoising and anomaly detection based on low-rank and sparse representations

Reference 53

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