H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 31 Citations 4,864 209 World Ranking 8119 National Ranking 771

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Zhaoxiang Zhang mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Feature. As part of his studies on Artificial intelligence, he frequently links adjacent subjects like Machine learning. His study in the field of Projection, Cognitive neuroscience of visual object recognition, Face and Facial recognition system is also linked to topics like Gait analysis.

In his study, which falls under the umbrella issue of Pattern recognition, Detector is strongly linked to Contextual image classification. Zhaoxiang Zhang combines subjects such as Supervised learning, Recurrent neural network and Histogram with his study of Feature extraction. The study incorporates disciplines such as Particle filter, Head and Segmentation, Image segmentation in addition to Histogram.

His most cited work include:

  • Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection (292 citations)
  • ASTER Global Digital Elevation Model Version 2 - summary of validation results (279 citations)
  • Scale-Aware Trident Networks for Object Detection (227 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Machine learning. Artificial intelligence is a component of his Robustness, Object detection, Feature, Discriminative model and Convolutional neural network studies. His work carried out in the field of Convolutional neural network brings together such families of science as Generalization and Training set.

His Pattern recognition research focuses on Contextual image classification and how it relates to Cognitive neuroscience of visual object recognition. His Feature extraction research is multidisciplinary, incorporating perspectives in Histogram, Image, Feature and Representation. His work on Gait analysis as part of general Gait study is frequently linked to Hidden Markov model, bridging the gap between disciplines.

He most often published in these fields:

  • Artificial intelligence (87.45%)
  • Pattern recognition (44.71%)
  • Computer vision (37.65%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (87.45%)
  • Pattern recognition (44.71%)
  • Feature extraction (23.53%)

In recent papers he was focusing on the following fields of study:

His main research concerns Artificial intelligence, Pattern recognition, Feature extraction, Segmentation and Domain. His Artificial intelligence research integrates issues from Machine learning and Computer vision. His Machine learning study combines topics from a wide range of disciplines, such as Sparse approximation and Face.

Many of his research projects under Computer vision are closely connected to Construct with Construct, tying the diverse disciplines of science together. The concepts of his Pattern recognition study are interwoven with issues in Data modeling, Image sensor, Color constancy, Pixel and Object. The Feature extraction study combines topics in areas such as Matching, Visualization, Image and Similarity.

Between 2019 and 2021, his most popular works were:

  • SARPNET: Shape attention regional proposal network for liDAR-based 3D object detection (19 citations)
  • CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation (18 citations)
  • Learning Integral Objects With Intra-Class Discriminator for Weakly-Supervised Semantic Segmentation (16 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary areas of investigation include Artificial intelligence, Pattern recognition, Segmentation, Feature extraction and Embedding. His study in Leverage, Benchmark, Feature, Object detection and Feature falls under the purview of Artificial intelligence. His studies in Benchmark integrate themes in fields like Orientation, Point cloud, Computer vision, Encoder and Lidar.

Zhaoxiang Zhang interconnects Object, Pixel and Discriminator in the investigation of issues within Pattern recognition. His Feature extraction research is multidisciplinary, relying on both Discriminative model and Inference. His Embedding research incorporates elements of Margin, Variation and Code.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Scale-Aware Trident Networks for Object Detection

Yanghao Li;Yuntao Chen;Naiyan Wang;Zhao-Xiang Zhang.
international conference on computer vision (2019)

326 Citations

Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection

Min Li;Zhaoxiang Zhang;Kaiqi Huang;Tieniu Tan.
international conference on pattern recognition (2008)

320 Citations

Three-Dimensional Deformable-Model-Based Localization and Recognition of Road Vehicles

Zhaoxiang Zhang;Tieniu Tan;Kaiqi Huang;Yunhong Wang.
IEEE Transactions on Image Processing (2012)

167 Citations

GIFT: A Real-Time and Scalable 3D Shape Search Engine

Song Bai;Xiang Bai;Zhichao Zhou;Zhaoxiang Zhang.
computer vision and pattern recognition (2016)

159 Citations

DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer.

Yuntao Chen;Naiyan Wang;Zhaoxiang Zhang.
national conference on artificial intelligence (2018)

120 Citations

Incremental Learning for Video-Based Gait Recognition With LBP Flow

Maodi Hu;Yunhong Wang;Zhaoxiang Zhang;De Zhang.
IEEE Transactions on Systems, Man, and Cybernetics (2013)

118 Citations

Rapid and robust human detection and tracking based on omega-shape features

Min Li;Zhaoxiang Zhang;Kaiqi Huang;Tieniu Tan.
international conference on image processing (2009)

116 Citations

Hierarchical Convolutional Neural Networks for EEG-Based Emotion Recognition

Jinpeng Li;Zhaoxiang Zhang;Huiguang He.
Cognitive Computation (2018)

111 Citations

Hard-Aware Point-to-Set Deep Metric for Person Re-identification

Rui Yu;Zhiyong Dou;Song Bai;Zhaoxiang Zhang.
european conference on computer vision (2018)

110 Citations

View-Invariant Discriminative Projection for Multi-View Gait-Based Human Identification

Maodi Hu;Yunhong Wang;Zhaoxiang Zhang;James J. Little.
IEEE Transactions on Information Forensics and Security (2013)

106 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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