Guangshuai Gao

About Guangshuai Gao

Guangshuai Gao, With an exceptional h-index of 14 and a recent h-index of 14 (since 2020), a distinguished researcher at Beihang University, specializes in the field of Image processing, pattern recognation, machine learning, computer vision, remote sensing analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

YOLC: You Only Look Clusters for Tiny Object Detection in Aerial Images

Optical Remote Sensing Object Detection Based on Background Separation and Small Object Compensation Strategy

A Key Feature-Enhanced Network for Remote Sensing Object Detection

Building detection from panchromatic and multispectral images with dual-stream asymmetric fusion networks

AFSPNet: an adaptive feature selection pyramid network for efficient object detection in remote sensing images

Context-aware cross-level attention fusion network for infrared small target detection

PSGCNet: A pyramidal scale and global context guided network for dense object counting in remote-sensing images

MRDet: A multihead network for accurate rotated object detection in aerial images

Guangshuai Gao Information

University

Position

___

Citations(all)

564

Citations(since 2020)

549

Cited By

140

hIndex(all)

14

hIndex(since 2020)

14

i10Index(all)

15

i10Index(since 2020)

15

Email

University Profile Page

Google Scholar

Guangshuai Gao Skills & Research Interests

Image processing

pattern recognation

machine learning

computer vision

remote sensing analysis

Top articles of Guangshuai Gao

YOLC: You Only Look Clusters for Tiny Object Detection in Aerial Images

IEEE Transactions on Intelligent Transportation Systems

2024/4/23

Optical Remote Sensing Object Detection Based on Background Separation and Small Object Compensation Strategy

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

2024/1/9

A Key Feature-Enhanced Network for Remote Sensing Object Detection

2023/10/8

Building detection from panchromatic and multispectral images with dual-stream asymmetric fusion networks

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

2023/3/27

AFSPNet: an adaptive feature selection pyramid network for efficient object detection in remote sensing images

Journal of Applied Remote Sensing

2022/10/1

Context-aware cross-level attention fusion network for infrared small target detection

Journal of Applied Remote Sensing

2022/10/1

PSGCNet: A pyramidal scale and global context guided network for dense object counting in remote-sensing images

IEEE Transactions on Geoscience and Remote Sensing

2022/2/24

MRDet: A multihead network for accurate rotated object detection in aerial images

IEEE Transactions on Geoscience and Remote Sensing

2021/10/1

Multi-scale global contrast CNN for salient object detection

Sensors

2020/5/6

Co-saliency detection with co-attention fully convolutional network

IEEE Transactions on Circuits and Systems for Video Technology

2020/5/4

Counting dense objects in remote sensing images

2020/5/4

Cnn-based density estimation and crowd counting: A survey

arXiv preprint arXiv:2003.12783

2020/3/28

Unsupervised conditional disentangle network for image dehazing

2020/10/25

Counting from sky: A large-scale data set for remote sensing object counting and a benchmark method

IEEE Transactions on geoscience and remote sensing

2020/9/18

See List of Professors in Guangshuai Gao University(Beihang University)