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Hierarchical Residual Attention Network for Single Image Super-Resolution
Convolutional neural networks are the most successful models in single i...
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Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery
Cattle farming is responsible for 8.8% of greenhouse gas emissions world...
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Affinity LCFCN: Learning to Segment Fish with Weak Supervision
Aquaculture industries rely on the availability of accurate fish body me...
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Synbols: Probing Learning Algorithms with Synthetic Datasets
Progress in the field of machine learning has been fueled by the introdu...
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CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions
In the last few years, we have witnessed a renewed and fast-growing inte...
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OverNet: Lightweight Multi-Scale Super-Resolution with Overscaling Network
Super-resolution (SR) has achieved great success due to the development ...
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A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images
Acquiring count annotations generally requires less human effort than po...
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LOOC: Localize Overlapping Objects with Count Supervision
Acquiring count annotations generally requires less human effort than po...
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Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning
Learning from non-stationary data remains a great challenge for machine ...
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Embedding Propagation: Smoother Manifold for Few-Shot Classification
Few-shot classification is challenging because the data distribution of ...
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Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery
We propose a novel attention mechanism to enhance Convolutional Neural N...
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Beyond One-hot Encoding: lower dimensional target embedding
Target encoding plays a central role when learning Convolutional Neural ...
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TADAM: Task dependent adaptive metric for improved few-shot learning
Few-shot learning has become essential for producing models that general...
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Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks
Social media, as a major platform for communication and information exch...
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Regularizing CNNs with Locally Constrained Decorrelations
Regularization is key for deep learning since it allows training more co...
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