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08/14/2023
Channel-Wise Contrastive Learning for Learning with Noisy Labels
In real-world datasets, noisy labels are pervasive. The challenge of lea...
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07/11/2023
Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels
In recent years, research on learning with noisy labels has focused on d...
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05/16/2023
Security Enhancement of Quantum Noise Stream Cipher Based on Probabilistic Constellation Shaping
We propose a QNSC pre-coding scheme based on probabilistic shaping of th...
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05/08/2023
Recovering the Block-wise Relationship in an Encryption-Then-Compression System
Joint encryption and compression is an ideal solution for protecting sec...
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04/25/2023
LEMaRT: Label-Efficient Masked Region Transform for Image Harmonization
We present a simple yet effective self-supervised pre-training method fo...
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12/28/2022
Swin MAE: Masked Autoencoders for Small Datasets
The development of deep learning models in medical image analysis is maj...
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12/23/2022
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse
With the ever-growing model size and the limited availability of labeled...
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12/07/2022
PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels
Convolutional Neural Networks (CNNs) have demonstrated superiority in le...
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12/02/2022
Avoiding spurious correlations via logit correction
Empirical studies suggest that machine learning models trained with empi...
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11/02/2022
Recovering Sign Bits of DCT Coefficients in Digital Images as an Optimization Problem
Recovering unknown, missing, damaged, distorted or lost information in D...
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10/04/2022
Are All Losses Created Equal: A Neural Collapse Perspective
While cross entropy (CE) is the most commonly used loss to train deep ne...
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08/14/2022
Cryptanalyzing an Image Encryption Algorithm Underpinned by 2D Lag-Complex Logistic Map
This paper analyzes security performance of an image encryption algorith...
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06/17/2022
Video Shadow Detection via Spatio-Temporal Interpolation Consistency Training
It is challenging to annotate large-scale datasets for supervised video ...
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06/14/2022
Asymmetric Dual-Decoder U-Net for Joint Rain and Haze Removal
This work studies the joint rain and haze removal problem. In real-life ...
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06/07/2022
Parotid Gland MRI Segmentation Based on Swin-Unet and Multimodal Images
Parotid gland tumors account for approximately 2 tumors. Preoperative tu...
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04/05/2022
Depth-Guided Sparse Structure-from-Motion for Movies and TV Shows
Existing approaches for Structure from Motion (SfM) produce impressive 3...
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03/03/2022
On Learning Contrastive Representations for Learning with Noisy Labels
Deep neural networks are able to memorize noisy labels easily with a sof...
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02/28/2022
Robust Training under Label Noise by Over-parameterization
Recently, over-parameterized deep networks, with increasingly more netwo...
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12/28/2021
Uncertainty Detection in EEG Neural Decoding Models
EEG decoding systems based on deep neural networks have been widely used...
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10/07/2021
Adaptive Early-Learning Correction for Segmentation from Noisy Annotations
Deep learning in the presence of noisy annotations has been studied exte...
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09/24/2021
Cryptanalyzing two image encryption algorithms based on a first-order time-delay system
Security is a key problem for the transmission, interchange and storage ...
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08/15/2021
Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning
Fine-grained action recognition is attracting increasing attention due t...
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08/08/2021
OVIS: Open-Vocabulary Visual Instance Search via Visual-Semantic Aligned Representation Learning
We introduce the task of open-vocabulary visual instance search (OVIS). ...
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07/27/2021
Multiperiod Dispatching and Routing for On-Time Delivery in a Dynamic and Stochastic Environment
On-demand delivery has become increasingly popular around the world. Bri...
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06/23/2021
Multi-modal and frequency-weighted tensor nuclear norm for hyperspectral image denoising
Low-rankness is important in the hyperspectral image (HSI) denoising tas...
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03/01/2021
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training
Normalization techniques have become a basic component in modern convolu...
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01/19/2021
Hyperspectral Image Restoration via Multi-mode and Double-weighted Tensor Nuclear Norm Minimization
Tensor nuclear norm (TNN) induced by tensor singular value decomposition...
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12/22/2020
Adversarial Multiscale Feature Learning for Overlapping Chromosome Segmentation
Chromosome karyotype analysis is of great clinical importance in the dia...
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12/03/2020
Multi-mode Core Tensor Factorization based Low-Rankness and Its Applications to Tensor Completion
Low-rank tensor completion has been widely used in computer vision and m...
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08/21/2020
Urban Bike Lane Planning with Bike Trajectories: Models, Algorithms, and a Real-World Case Study
We study an urban bike lane planning problem based on the fine-grained b...
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06/30/2020
Early-Learning Regularization Prevents Memorization of Noisy Labels
We propose a novel framework to perform classification via deep learning...
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06/24/2020
Spatial Pattern Recognition with Adjacency-Clustering: Improved Diagnostics for Semiconductor Wafer Bin Maps
In semiconductor manufacturing, statistical quality control hinges on an...
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05/14/2020
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition
Skeleton-based action recognition has attracted increasing attention due...
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12/30/2019
Text Steganalysis with Attentional LSTM-CNN
With the rapid development of Natural Language Processing (NLP) technolo...
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11/09/2019
On the design of convolutional neural networks for automatic detection of Alzheimer's disease
Early detection is a crucial goal in the study of Alzheimer's Disease (A...
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11/02/2019
FCEM: A Novel Fast Correlation Extract Model For Real Time Steganalysis of VoIP Stream via Multi-head Attention
Extracting correlation features between codes-words with high computatio...
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09/15/2019
Machine Discovery of Partial Differential Equations from Spatiotemporal Data
The study presents a general framework for discovering underlying Partia...
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05/12/2019
Sparse Recovery Beyond Compressed Sensing: Separable Nonlinear Inverse Problems
Extracting information from nonlinear measurements is a fundamental chal...
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04/09/2019
Time-Series Analysis via Low-Rank Matrix Factorization: Applied to Infant-Sleep Data
We propose a nonparametric model for time series with missing data based...
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09/06/2018
Discovering Influential Factors in Variational Autoencoder
In the field of machine learning, it is still a critical issue to identi...
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03/05/2018