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07/14/2023
Learning Sparse Neural Networks with Identity Layers
The sparsity of Deep Neural Networks is well investigated to maximize th...
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06/08/2023
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification
Unsupervised person re-identification has achieved great success through...
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04/21/2023
Picking Up Quantization Steps for Compressed Image Classification
The sensitivity of deep neural networks to compressed images hinders the...
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04/02/2023
Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning
Few-shot class-incremental learning (FSCIL) aims at learning to classify...
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01/27/2023
Training Full Spike Neural Networks via Auxiliary Accumulation Pathway
Due to the binary spike signals making converting the traditional high-p...
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03/10/2022
Annotation Efficient Person Re-Identification with Diverse Cluster-Based Pair Selection
Person Re-identification (Re-ID) has attracted great attention due to it...
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01/21/2022
Deep Reinforcement Learning with Spiking Q-learning
With the help of special neuromorphic hardware, spiking neural networks ...
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08/19/2021
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
Recently, the generalization behavior of Convolutional Neural Networks (...
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03/01/2021
Adversarial Reciprocal Points Learning for Open Set Recognition
Open set recognition (OSR), aiming to simultaneously classify the seen c...
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01/04/2021
Variationally and Intrinsically motivated reinforcement learning for decentralized traffic signal control
One of the biggest challenges in multi-agent reinforcement learning is c...
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10/31/2020
Learning Open Set Network with Discriminative Reciprocal Points
Open set recognition is an emerging research area that aims to simultane...
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05/25/2019
Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification
Person re-identification (Re-ID) across multiple datasets is a challengi...
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12/05/2018
