FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition | Paper Citation Record

Observation 88d8ef8d-3347-4c7c-b82c-016d86e4c960 · outbound

This paper cites Fish-vista: A multi-purpose dataset for understanding & identification of traits from images,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Fish-vista: A multi-purpose dataset for understanding & identification of traits from images,

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This paper cites Autofish: Dataset and benchmark for fine-grained analysis of fish,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Autofish: Dataset and benchmark for fine-grained analysis of fish,

Reference 2

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This paper cites M4FT: Mamba, migratory, mobile and multiple fish tracking,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition M4FT: Mamba, migratory, mobile and multiple fish tracking,

Reference 3

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This paper cites Fishnet: A large-scale dataset and benchmark for fish recognition, detection, and functional trait prediction,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Fishnet: A large-scale dataset and benchmark for fish recognition, detection, and functional trait prediction,

Reference 4

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This paper cites A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis,

Reference 5

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This paper cites The deepfish computer vision dataset for fish instance segmentation, classification, and size estimation,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition The deepfish computer vision dataset for fish instance segmentation, classification, and size estimation,

Reference 6

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Observation 1e6c3609-1392-4411-840b-8b4b106811d3 · outbound

This paper cites Automatic estuarine fish species classification system based on deep learning techniques,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Automatic estuarine fish species classification system based on deep learning techniques,

Reference 7

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This paper cites Fish tracking and segmentation from stereo videos on the wild sea surface for electronic monitoring of rail fishing,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Fish tracking and segmentation from stereo videos on the wild sea surface for electronic monitoring of rail fishing,

Reference 8

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This paper cites Fish tracking and continual behavioral pattern clustering using novel sillago sihama vid (ssvid),.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Fish tracking and continual behavioral pattern clustering using novel sillago sihama vid (ssvid),

Reference 9

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This paper cites Fishnet: Fish visual recognition with one stage multi-task learning,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Fishnet: Fish visual recognition with one stage multi-task learning,

Reference 10

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Observation 0bfd21b4-4693-46a3-8e26-0ce71d68c102 · outbound

This paper cites Mtaffb: a multi-task active learning framework for analyzing fish school feeding behavior,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Mtaffb: a multi-task active learning framework for analyzing fish school feeding behavior,

Reference 11

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This paper cites Exploring simple siamese representation learning,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Exploring simple siamese representation learning,

Reference 12

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This paper cites Interpretable image classi- fication via non-parametric part prototype learning,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Interpretable image classi- fication via non-parametric part prototype learning,

Reference 13

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Observation 73e488f2-1129-481f-82b7-d596340de9e2 · outbound

This paper cites Multi-task learning using uncer- tainty to weigh losses for scene geometry and semantics,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Multi-task learning using uncer- tainty to weigh losses for scene geometry and semantics,

Reference 14

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This paper cites Wildfish++: A comprehensive fish benchmark for multimedia research,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Wildfish++: A comprehensive fish benchmark for multimedia research,

Reference 15

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This paper cites Fine-grained fish classification from small to large datasets with vision transformers,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Fine-grained fish classification from small to large datasets with vision transformers,

Reference 16

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This paper cites A lightweight fine-grained pelagic fish recognition algorithm based on object detec- tion,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition A lightweight fine-grained pelagic fish recognition algorithm based on object detec- tion,

Reference 17

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This paper cites BioCLIP: A vision foundation model for the tree of life,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition BioCLIP: A vision foundation model for the tree of life,

Reference 18

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This paper cites Yolo-fd: An accurate fish disease detection method based on multi-task learning,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Yolo-fd: An accurate fish disease detection method based on multi-task learning,

Reference 19

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This paper cites Deepseavision: Enhanced detection and classification of underwater species,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Deepseavision: Enhanced detection and classification of underwater species,

Reference 20

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This paper cites Optimizing fish classification with a hybrid sae-svm model: Perfor- mance and evaluation on fish-gres and fish4-knowledge datasets,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Optimizing fish classification with a hybrid sae-svm model: Perfor- mance and evaluation on fish-gres and fish4-knowledge datasets,

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This paper cites Which tasks should be learned together in multi-task learning?.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Which tasks should be learned together in multi-task learning?

Reference 22

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Model- protected multi-task learning,

Reference 23

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This paper cites Decoupling representation learning and classifier for long- tailed adversarial training,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Decoupling representation learning and classifier for long- tailed adversarial training,

Reference 24

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This paper cites Gradient surgery for multi-task learning,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Gradient surgery for multi-task learning,

Reference 25

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This paper cites Individual fish recognition method with coarse and fine-grained feature linkage learning for precision aquaculture,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Individual fish recognition method with coarse and fine-grained feature linkage learning for precision aquaculture,

Reference 26

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This paper cites Hierarchical feature attention learning network for detecting object and discriminative parts in fine-grained visual classification,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Hierarchical feature attention learning network for detecting object and discriminative parts in fine-grained visual classification,

Reference 27

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Concept bottleneck models,

Reference 28

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Very deep convolutional networks for large-scale image recognition,

Reference 29

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Aggregated residual transformations for deep neural networks,

Reference 30

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Designing network design spaces,

Reference 31

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 32

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 33

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Maxvit: Multi-axis vision transformer,

Reference 34

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This paper cites Learning transferable visual models from natural language supervision,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Learning transferable visual models from natural language supervision,

Reference 35

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition DINOv2: Learning robust visual features without supervision,

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition A simple interpretable transformer for fine-grained image classification and analysis,

Reference 37

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Transfg: A transformer architecture for fine-grained recognition,

Reference 38

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Pyramid scene parsing network,

Reference 39

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Encoder- decoder with atrous separable convolution for semantic image segmen- tation,

Reference 40

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Per-pixel classification is not all you need for semantic segmentation,

Reference 41

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Yolov8: A novel object detection algorithm with enhanced performance and robustness,

Reference 42

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This paper cites Molmo and pixmo: Open weights and open data for state-of-the-art vision-language models,.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Molmo and pixmo: Open weights and open data for state-of-the-art vision-language models,

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This paper cites Query2Label: A Simple Transformer Way to Multi-Label Classification.

FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Query2Label: A Simple Transformer Way to Multi-Label Classification

Reference 44

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition GradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks,

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 46

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FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition Visualizing data using t-sne

Reference 47

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