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08/04/2023
Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning
Deep Neural Network (DNN) has achieved great success on datasets of clos...
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07/18/2023
Towards Trustworthy Dataset Distillation
Efficiency and trustworthiness are two eternal pursuits when applying de...
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03/30/2023
OpenMix: Exploring Outlier Samples for Misclassification Detection
Reliable confidence estimation for deep neural classifiers is a challeng...
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03/21/2023
Dynamic-Aware Loss for Learning with Label Noise
Label noise poses a serious threat to deep neural networks (DNNs). Emplo...
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03/14/2023
Nonlinear Hyperspectral Unmixing based on Multilinear Mixing Model using Convolutional Autoencoders
Unsupervised spectral unmixing consists of representing each observed pi...
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03/06/2023
Rethinking Confidence Calibration for Failure Prediction
Reliable confidence estimation for the predictions is important in many ...
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03/02/2023
Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detection
Detecting Out-of-distribution (OOD) inputs have been a critical issue fo...
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10/20/2022
Robust Multi-Read Reconstruction from Contaminated Clusters Using Deep Neural Network for DNA Storage
DNA has immense potential as an emerging data storage medium. The princi...
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04/01/2020
Boosting Deep Hyperspectral Image Classification with Spectral Unmixing
Recent advances in neural networks have made great progress in addressin...
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01/31/2018
A CNN-based Spatial Feature Fusion Algorithm for Hyperspectral Imagery Classification
The shortage of training samples remains one of the main obstacles in ap...
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11/20/2017
Spectral-Spatial Feature Extraction and Classification by ANN Supervised with Center Loss in Hyperspectral Imagery
In this paper, we propose a spectral-spatial feature extraction and clas...
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02/04/2016
Correntropy Maximization via ADMM - Application to Robust Hyperspectral Unmixing
In hyperspectral images, some spectral bands suffer from low signal-to-n...
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01/22/2015
Bi-Objective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models
Nonnegative matrix factorization (NMF) is a powerful class of feature ex...
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07/16/2014
