Area of research
Artificial Intelligence · Computer Vision and Pattern Recognition
Research interest
Research interests include Computer science, Artificial intelligence, Pattern recognition (psychology), Benchmark (surveying), Feature (linguistics), and Regularization (linguistics).
Singular Value Decomposition-Driven Non-negative Matrix Factorization with Application to Identify the Association Patterns of Sarcoma Recurrence
Structural Subspace Learning for Few-shot Fine-grained Recognition
Prediction of cooling effect of constant temperature community bin based on BP neural network
Feature Transformation for Cross-domain Few-Shot Remote Sensing Scene Classification
Catalytic co-pyrolysis characteristics and kinetics analysis of food waste and chinar leaves, and the large-scale microwave disposal feasibility
Robust Recovery of Low Rank Matrix by Nonconvex Rank Regularization
Learning Semantically Enhanced Feature for Fine-Grained Image Classification
Learning Semantically Enhanced Feature for Fine-Grained Image Classification
Label-Smooth Learning for Fine-Grained Visual Categorization
The Effectiveness of Noise in Data Augmentation for Fine-Grained Image Classification
Cross-X Learning for Fine-Grained Visual Categorization
Exploiting Category-Level Semantic Relationships for Fine-Grained Image Recognition
Cross-Category Cross-Semantic Regularization for Fine-Grained Image Recognition
Intelligent Cashmere/Wool Classification with Convolutional Neural Network
Convolutional Sparse Autoencoders for Image Classification
Nonconvex relaxation based matrix regression for face recognition with structural noise and mixed noise
Sparseness Analysis in the Pretraining of Deep Neural Networks