228 citations · 341 across the 13 of their papers we have counts for
13 papers
Grafting Transformer on Automatically Designed Convolutional Neural Network for Hyperspectral Image Classification
Xizhe Xue, Haokui Zhang, Bei Fang +2
Hyperspectral image (HSI) classification has been a hot topic for decides, as hyperspectral images have rich spatial and spectral information and provide strong basis for distingui…
DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network
Xizhe Xue, Ying Li, Xiaoyue Yin +1
Discriminative correlation filters (DCF) and siamese networks have achieved promising performance on visual tracking tasks thanks to their superior computational efficiency and rel…
3D-ANAS: 3D Asymmetric Neural Architecture Search for Fast Hyperspectral Image Classification
Haokui Zhang, Chengrong Gong, Yunpeng Bai +2
Hyperspectral images involve abundant spectral and spatial information, playing an irreplaceable role in land-cover classification. Recently, based on deep learning technologies, a…
Hyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning
Haokui Zhang, Ying Li, Yenan Jiang +3
Recently, hyperspectral image (HSI) classification approaches based on deep learning (DL) models have been proposed and shown promising performance. However, because of very limite…
Memory-Efficient Hierarchical Neural Architecture Search for Image Restoration
Haokui Zhang, Ying Li, Hao Chen +3
Recently, much attention has been spent on neural architecture search (NAS), aiming to outperform those manually-designed neural architectures on high-level vision recognition task…
Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map
Xizhe Xue, Ying Li, Qiang Shen
Benefiting from its ability to efficiently learn how an object is changing, correlation filters have recently demonstrated excellent performance for rapidly tracking objects. Desig…
Hyperspectral Image Classification with Spatial Consistence Using Fully Convolutional Spatial Propagation Network
Yenan Jiang, Ying Li, Shanrong Zou +2
In recent years, deep convolutional neural networks (CNNs) have shown impressive ability to represent hyperspectral images (HSIs) and achieved encouraging results in HSI classifica…
Locality-Aware Rotated Ship Detection in High-Resolution Remote Sensing Imagery Based on Multi-Scale Convolutional Network
Lingyi Liu, Yunpeng Bai, Ying Li
Ship detection has been an active and vital topic in the field of remote sensing for a decade, but it is still a challenging problem due to the large scale variations, the high asp…
Multispectral Pan-sharpening via Dual-Channel Convolutional Network with Convolutional LSTM Based Hierarchical Spatial-Spectral Feature Fusion
Dong Wang, Yunpeng Bai, Ying Li
Multispectral pan-sharpening aims at producing a high resolution (HR) multispectral (MS) image in both spatial and spectral domains by fusing a panchromatic (PAN) image and a corre…
Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning
Haokui Zhang, Yu Liu, Bei Fang +3
Hyperspectral image(HSI) classification has been improved with convolutional neural network(CNN) in very recent years. Being different from the RGB datasets, different HSI datasets…
Memory-Efficient Hierarchical Neural Architecture Search for Image Denoising
Haokui Zhang, Ying Li, Hao Chen +1
Recently, neural architecture search (NAS) methods have attracted much attention and outperformed manually designed architectures on a few high-level vision tasks. In this paper, w…
Exploiting temporal consistency for real-time video depth estimation
Haokui Zhang, Chunhua Shen, Ying Li +3
Accuracy of depth estimation from static images has been significantly improved recently, by exploiting hierarchical features from deep convolutional neural networks (CNNs). Compar…
RGB-D Based Action Recognition with Light-weight 3D Convolutional Networks
Haokui Zhang, Ying Li, Peng Wang +2
Different from RGB videos, depth data in RGB-D videos provide key complementary information for tristimulus visual data which potentially could achieve accuracy improvement for act…