activity
20182021
most citedHyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning

228 citations · 237 across the 7 of their papers we have counts for

collaborators

11 papers

cs.CV2021

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…

cs.CV2020228 cited

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…

cs.CV2020

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…

cs.CV2020

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…

cs.CV20202 cited

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…

cs.CV20201 cited

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…