H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 79 Citations 26,332 613 World Ranking 487 National Ranking 1

Research.com Recognitions

Awards & Achievements

2021 - IEEE Fellow For contributions to computer vision and representation learning

2018 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to human action recognition and video understanding

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Ling Shao mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Discriminative model. His research links Machine learning with Artificial intelligence. His work deals with themes such as Contextual image classification and Kernel, which intersect with Pattern recognition.

His Computer vision research integrates issues from Field and Salient. His work carried out in the field of Feature extraction brings together such families of science as Feature, Artificial neural network, Speech recognition, Hidden Markov model and Dimensionality reduction. Ling Shao has researched Discriminative model in several fields, including Subspace topology, Embedding, Probabilistic logic and Robustness.

His most cited work include:

  • Enhanced Computer Vision With Microsoft Kinect Sensor: A Review (1123 citations)
  • A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior (729 citations)
  • A survey on fall detection: Principles and approaches (528 citations)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Discriminative model. His work in Segmentation, Feature extraction, Deep learning, Feature and Image are all subfields of Artificial intelligence research. His work carried out in the field of Pattern recognition brings together such families of science as Contextual image classification, Hash function and Robustness.

The Hash function study combines topics in areas such as Binary code and Image retrieval. His biological study spans a wide range of topics, including Salient and Detector. His study in Machine learning is interdisciplinary in nature, drawing from both Visualization, Representation, Inference and Training set.

He most often published in these fields:

  • Artificial intelligence (76.92%)
  • Pattern recognition (35.74%)
  • Computer vision (26.04%)

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

  • Artificial intelligence (76.92%)
  • Pattern recognition (35.74%)
  • Machine learning (20.36%)

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

Ling Shao spends much of his time researching Artificial intelligence, Pattern recognition, Machine learning, Segmentation and Discriminative model. His study looks at the relationship between Artificial intelligence and topics such as Computer vision, which overlap with Artificial neural network. His study looks at the intersection of Pattern recognition and topics like Embedding with Class.

As a part of the same scientific study, he usually deals with the Machine learning, concentrating on Code and frequently concerns with Algorithm. The various areas that Ling Shao examines in his Object study include Field and Salient. His work deals with themes such as Weighting, Pedestrian detection and Feature learning, which intersect with Feature.

Between 2019 and 2021, his most popular works were:

  • Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images (139 citations)
  • Deep Learning for Person Re-identification: A Survey and Outlook (85 citations)
  • HRank: Filter Pruning Using High-Rank Feature Map (72 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Ling Shao focuses on Artificial intelligence, Pattern recognition, Segmentation, Discriminative model and Machine learning. The study of Artificial intelligence is intertwined with the study of Computer vision in a number of ways. His Pattern recognition research is multidisciplinary, incorporating elements of Embedding, Face, Contextual image classification, Channel and Benchmark.

His Segmentation study which covers Object detection that intersects with Pyramid, Speedup and Feature extraction. His Discriminative model study combines topics from a wide range of disciplines, such as Semantics, Linear subspace and Visualization. His research integrates issues of Image resolution and Inference in his study of Machine learning.

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

Enhanced Computer Vision With Microsoft Kinect Sensor: A Review

Jungong Han;Ling Shao;Dong Xu;Jamie Shotton.
IEEE Transactions on Systems, Man, and Cybernetics (2013)

1673 Citations

A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior

Qingsong Zhu;Jiaming Mai;Ling Shao.
IEEE Transactions on Image Processing (2015)

984 Citations

A survey on fall detection: Principles and approaches

Muhammad Mubashir;Ling Shao;Luke Seed.
Neurocomputing (2013)

782 Citations

Recent advances and trends in visual tracking: A review

Hanxuan Yang;Ling Shao;Feng Zheng;Liang Wang.
Neurocomputing (2011)

724 Citations

A rapid learning algorithm for vehicle classification

Xuezhi Wen;Ling Shao;Yu Xue;Wei Fang.
Information Sciences (2015)

488 Citations

Video Salient Object Detection via Fully Convolutional Networks

Wenguan Wang;Jianbing Shen;Ling Shao.
IEEE Transactions on Image Processing (2018)

422 Citations

Design and performance evaluation of a whole-body Ingenuity TF PET-MRI system

Habib Zaidi;N Ojha;M Morich;J Griesmer.
Physics in Medicine and Biology (2011)

397 Citations

Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition

Di Wu;Lionel Pigou;Pieter-Jan Kindermans;Nam Do-Hoang Le.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2016)

376 Citations

Transfer Learning for Visual Categorization: A Survey

Ling Shao;Fan Zhu;Xuelong Li.
IEEE Transactions on Neural Networks (2015)

345 Citations

From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms

Ling Shao;Ruomei Yan;Xuelong Li;Yan Liu.
IEEE Transactions on Systems, Man, and Cybernetics (2014)

336 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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