activity
20182020
most citedMultiResolution Attention Extractor for Small Object Detection

8 citations · 10 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV20208 cited

MultiResolution Attention Extractor for Small Object Detection

Fan Zhang, Licheng Jiao, Lingling Li +2

Small objects are difficult to detect because of their low resolution and small size. The existing small object detection methods mainly focus on data preprocessing or narrowing th…

cs.CV2019

A Survey of Deep Learning-based Object Detection

Licheng Jiao, Fan Zhang, Fang Liu +4

Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in peoples life, such as monitoring security, autonomous dr…

cs.CV2019

Pixel DAG-Recurrent Neural Network for Spectral-Spatial Hyperspectral Image Classification

Xiufang Li, Qigong Sun, Lingling Li +3

Exploiting rich spatial and spectral features contributes to improve the classification accuracy of hyperspectral images (HSIs). In this paper, based on the mechanism of the popula…

eess.IV20192 cited

Semi-supervised Complex-valued GAN for Polarimetric SAR Image Classification

Qigong Sun, Xiufang Li, Lingling Li +3

Polarimetric synthetic aperture radar (PolSAR) images are widely used in disaster detection and military reconnaissance and so on. However, their interpretation faces some challeng…

cs.CV2018

Modified Diversity of Class Probability Estimation Co-training for Hyperspectral Image Classification

Yan Ju, Lingling Li, Licheng Jiao +3

Due to the limited amount and imbalanced classes of labeled training data, the conventional supervised learning can not ensure the discrimination of the learned feature for hypersp…

cs.CV2018

Deep Adaptive Proposal Network for Object Detection in Optical Remote Sensing Images

Lin Cheng, Xu Liu, Lingling Li +2

Object detection is a fundamental and challenging problem in aerial and satellite image analysis. More recently, a two-stage detector Faster R-CNN is proposed and demonstrated to b…