Area of research
Computer Vision and Pattern Recognition · Artificial Intelligence
Research interest
Research interests include Computer science, Artificial intelligence, Hash function, Discriminative model, Autoencoder, and Sketch.
Microstructure, wear and friction behavior of CoCrAlTaY‐ <i>x</i> CNTs composite coatings deposited by laser‐induction hybrid cladding
Unsupervised Structure-Adaptive Graph Contrastive Learning
Carbon Emission Evaluation of Recycled Fine Aggregate Concrete Based on Life Cycle Assessment
Mutual Quantization for Cross-Modal Search with Noisy Labels
Multi-Sentence Auxiliary Adversarial Networks for Fine-Grained Text-to-Image Synthesis
Transferable Coupled Network for Zero-Shot Sketch-Based Image Retrieval
Deep Multiview Collaborative Clustering
Self-Training With Progressive Representation Enhancement for Unsupervised Cross-Domain Person Re-Identification
Multi-Task Consistency-Preserving Adversarial Hashing for Cross-Modal Retrieval
Heterogeneous Graph Attention Network for Unsupervised Multiple-Target Domain Adaptation
Progressive Cross-Modal Semantic Network for Zero-Shot Sketch-Based Image Retrieval
Learning Unseen Concepts via Hierarchical Decomposition and Composition
Staged Sketch-to-Image Synthesis via Semi-supervised Generative Adversarial Networks
Unsupervised Semantic-Preserving Adversarial Hashing for Image Search
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs
Two-Stream Deep Hashing With Class-Specific Centers for Supervised Image Search
Asymmetric Cross-Guided Attention Network for Actor and Action Video Segmentation From Natural Language Query
Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval
Triplet-Based Deep Hashing Network for Cross-Modal Retrieval
Semantic Structure-based Unsupervised Deep Hashing
Active Transfer Learning Network: A Unified Deep Joint Spectral–Spatial Feature Learning Model for Hyperspectral Image Classification
Shared Predictive Cross-Modal Deep Quantization
Adversarial Examples for Hamming Space Search
Bilevel Distance Metric Learning for Robust Image Recognition
Neural Information Processing Systems 2018cited by 23position: middle
Determination of polyoxin B in cucumber and soil using liquid chromatography tandem mass spectrometry coupled with a modified QuEChERS method
Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization
Active multi-kernel domain adaptation for hyperspectral image classification
Distributed Adaptive Binary Quantization for Fast Nearest Neighbor Search
Representative commodity for six leafy vegetables based on the determination of six pesticide residues by gas chromatography
Determination of propineb and its metabolites propylenethiourea and propylenediamine in banana and soil using gas chromatography with flame photometric detection and LC–MS/MS analysis