H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 92 Citations 33,027 436 World Ranking 230 National Ranking 4

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Convolutional neural network. Artificial intelligence is represented through his Segmentation, Feature extraction, Artificial neural network, Discriminative model and Pascal research. His Pattern recognition study combines topics in areas such as Feature, Pixel, Contextual image classification, Facial recognition system and Visualization.

His Computer vision research is multidisciplinary, incorporating perspectives in Support vector machine and Robustness. His Machine learning study which covers Benchmark that intersects with Recurrent neural network. Chunhua Shen usually deals with Convolutional neural network and limits it to topics linked to Conditional random field and Monocular.

His most cited work include:

  • RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation (1131 citations)
  • Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields (665 citations)
  • Supervised Discrete Hashing (630 citations)

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

Chunhua Shen mostly deals with Artificial intelligence, Pattern recognition, Machine learning, Segmentation and Computer vision. Convolutional neural network, Feature, Image, Discriminative model and Feature extraction are subfields of Artificial intelligence in which his conducts study. His Pattern recognition research integrates issues from Object detection, Pixel, Representation, Contextual image classification and Benchmark.

His studies deal with areas such as Classifier and Training set as well as Machine learning. In general Segmentation study, his work on Image segmentation often relates to the realm of Code, thereby connecting several areas of interest. His Computer vision research is multidisciplinary, relying on both Support vector machine and Robustness.

He most often published in these fields:

  • Artificial intelligence (79.26%)
  • Pattern recognition (43.03%)
  • Machine learning (21.36%)

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

  • Artificial intelligence (79.26%)
  • Pattern recognition (43.03%)
  • Segmentation (17.18%)

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

Chunhua Shen mainly focuses on Artificial intelligence, Pattern recognition, Segmentation, Code and Image. His work deals with themes such as Machine learning and Computer vision, which intersect with Artificial intelligence. His studies in Machine learning integrate themes in fields like Anomaly detection and Memorization.

Chunhua Shen studies Convolutional neural network which is a part of Pattern recognition. His Image segmentation study in the realm of Segmentation interacts with subjects such as Layer. His Image study combines topics in areas such as Artificial neural network and Metric.

Between 2019 and 2021, his most popular works were:

  • COVID-19 Screening on Chest X-ray Images Using Deep Learning based Anomaly Detection (169 citations)
  • PolarMask: Single Shot Instance Segmentation With Polar Representation (104 citations)
  • Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection (69 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Chunhua Shen spends much of his time researching Artificial intelligence, Pattern recognition, Segmentation, Object detection and Feature extraction. He merges Artificial intelligence with Code in his research. While the research belongs to areas of Pattern recognition, Chunhua Shen spends his time largely on the problem of Margin, intersecting his research to questions surrounding Ordinal regression and Training set.

His work on Image segmentation is typically connected to Layer as part of general Segmentation study, connecting several disciplines of science. His Object detection research is multidisciplinary, incorporating perspectives in Kernel, Contextual image classification and Matrix multiplication. Chunhua Shen has researched Feature extraction in several fields, including Computer engineering, Encoding, Minimum bounding box, Task analysis and Benchmark.

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

RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation

Guosheng Lin;Anton Milan;Chunhua Shen;Ian Reid.
computer vision and pattern recognition (2017)

1184 Citations

A survey of appearance models in visual object tracking

Xi Li;Weiming Hu;Chunhua Shen;Zhongfei Zhang.
ACM Transactions on Intelligent Systems and Technology (2013)

792 Citations

Deep convolutional neural fields for depth estimation from a single image

Fayao Liu;Chunhua Shen;Guosheng Lin.
computer vision and pattern recognition (2015)

758 Citations

Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

Fayao Liu;Chunhua Shen;Guosheng Lin;Ian Reid.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2016)

696 Citations

Supervised Discrete Hashing

Fumin Shen;Chunhua Shen;Wei Liu;Heng Tao Shen.
computer vision and pattern recognition (2015)

663 Citations

Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

Guosheng Lin;Chunhua Shen;Anton van den Hengel;Ian Reid.
computer vision and pattern recognition (2016)

635 Citations

FCOS: Fully Convolutional One-Stage Object Detection

Zhi Tian;Chunhua Shen;Hao Chen;Tong He.
international conference on computer vision (2019)

615 Citations

Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections

Xiao-Jiao Mao;Chunhua Shen;Yu-Bin Yang.
neural information processing systems (2016)

553 Citations

Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs

Bo Li;Chunhua Shen;Yuchao Dai;Anton van den Hengel.
computer vision and pattern recognition (2015)

441 Citations

What Value Do Explicit High Level Concepts Have in Vision to Language Problems

Qi Wu;Chunhua Shen;Lingqiao Liu;Anthony Dick.
computer vision and pattern recognition (2016)

433 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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Top Scientists Citing Chunhua Shen

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Dalian University of Technology

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Northwestern Polytechnical University

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