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11/23/2022
Learning Compact Features via In-Training Representation Alignment
Deep neural networks (DNNs) for supervised learning can be viewed as a p...
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12/14/2020
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints
Convolutional neural networks (CNNs) have achieved state-of-the-art perf...
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10/15/2020
Unsupervised Self-training Algorithm Based on Deep Learning for Optical Aerial Images Change Detection
Optical aerial images change detection is an important task in earth obs...
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07/12/2020
Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability
Latent factor collaborative filtering (CF) has been a widely used techni...
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03/04/2020
On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks
Deep convolutional neural networks (CNNs) trained with logistic and soft...
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02/23/2020
Improve SGD Training via Aligning Min-batches
Deep neural networks (DNNs) for supervised learning can be viewed as a p...
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02/23/2020
Improve SGD Training via Aligning Mini-batches
Deep neural networks (DNNs) for supervised learning can be viewed as a p...
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06/10/2019
CRCEN: A Generalized Cost-sensitive Neural Network Approach for Imbalanced Classification
Classification on imbalanced datasets is a challenging task in real-worl...
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06/09/2019
Interpreting Age Effects of Human Fetal Brain from Spontaneous fMRI using Deep 3D Convolutional Neural Networks
Understanding human fetal neurodevelopment is of great clinical importan...
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05/26/2019
Deep Representation Learning for Road Detection through Siamese Network
Robust road detection is a key challenge in safe autonomous driving. Rec...
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05/26/2019
Road Segmentation with Image-LiDAR Data Fusion
Robust road segmentation is a key challenge in self-driving research. Th...
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04/20/2017