H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 32 Citations 5,186 119 World Ranking 7492 National Ranking 695

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Algorithm

Lingxi Xie focuses on Artificial intelligence, Pattern recognition, Code, Segmentation and Contextual image classification. His work is dedicated to discovering how Artificial intelligence, Machine learning are connected with Encoding and other disciplines. Lingxi Xie has included themes like Object and Object detection in his Pattern recognition study.

His Code research is multidisciplinary, relying on both Stability, Regularization and Network architecture. His study in the field of Image segmentation also crosses realms of Variable and Fraction. The Contextual image classification study combines topics in areas such as Visual Word and Image texture.

His most cited work include:

  • Genetic CNN (372 citations)
  • CenterNet: Keypoint Triplets for Object Detection (359 citations)
  • Adversarial Examples for Semantic Segmentation and Object Detection (326 citations)

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

His primary areas of study are Artificial intelligence, Pattern recognition, Machine learning, Contextual image classification and Segmentation. His research investigates the connection between Artificial intelligence and topics such as Computer vision that intersect with issues in Adversarial system. In his research on the topic of Pattern recognition, Convolutional neural network is strongly related with Convolution.

His study looks at the relationship between Machine learning and fields such as Training set, as well as how they intersect with chemical problems. His work in Contextual image classification tackles topics such as Range which are related to areas like Fuzzy logic. His work on Object detection as part of general Object study is frequently linked to Class, bridging the gap between disciplines.

He most often published in these fields:

  • Artificial intelligence (82.68%)
  • Pattern recognition (43.58%)
  • Machine learning (21.23%)

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

  • Artificial intelligence (82.68%)
  • Machine learning (21.23%)
  • Pattern recognition (43.58%)

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

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Pattern recognition, Discriminative model and Code. His Artificial intelligence study incorporates themes from Key and Computer vision. Lingxi Xie has researched Machine learning in several fields, including Contextual image classification and Training set.

His study in Pattern recognition is interdisciplinary in nature, drawing from both Object detection and Quantization. Lingxi Xie combines subjects such as Regularization and Facial expression with his study of Discriminative model. His Code research incorporates elements of Network architecture and Computer engineering.

Between 2019 and 2021, his most popular works were:

  • PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search (93 citations)
  • Unsupervised Person Re-Identification via Softened Similarity Learning (23 citations)
  • Pruning from Scratch (17 citations)

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

  • Artificial intelligence
  • Machine learning
  • Algorithm

Lingxi Xie spends much of his time researching Artificial intelligence, Pattern recognition, Code, Computer engineering and Stability. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Computer vision. His research in the fields of Segmentation overlaps with other disciplines such as Image.

His Code study frequently involves adjacent topics like Image segmentation. Lingxi Xie interconnects Variation and Gradient estimation in the investigation of issues within Stability. The study incorporates disciplines such as Precision and recall, Monocular and Bounding overwatch in addition to Object.

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

Genetic CNN

Lingxi Xie;Alan Yuille.
international conference on computer vision (2017)

579 Citations

Adversarial Examples for Semantic Segmentation and Object Detection

Cihang Xie;Jianyu Wang;Zhishuai Zhang;Yuyin Zhou.
international conference on computer vision (2017)

433 Citations

CenterNet: Keypoint Triplets for Object Detection

Kaiwen Duan;Song Bai;Lingxi Xie;Honggang Qi.
international conference on computer vision (2019)

368 Citations

Progressive Differentiable Architecture Search: Bridging the Depth Gap Between Search and Evaluation

Xin Chen;Lingxi Xie;Jun Wu;Qi Tian.
international conference on computer vision (2019)

256 Citations

A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans

Yuyin Zhou;Lingxi Xie;Wei Shen;Wei Shen;Yan Wang.
medical image computing and computer assisted intervention (2017)

196 Citations

DisturbLabel: Regularizing CNN on the Loss Layer

Lingxi Xie;Jingdong Wang;Zhen Wei;Meng Wang.
computer vision and pattern recognition (2016)

146 Citations

Image Classification and Retrieval are ONE

Lingxi Xie;Richang Hong;Bo Zhang;Qi Tian.
international conference on multimedia retrieval (2015)

145 Citations

Attention-Guided Unified Network for Panoptic Segmentation

Yanwei Li;Xinze Chen;Zheng Zhu;Lingxi Xie.
computer vision and pattern recognition (2019)

129 Citations

Recurrent Saliency Transformation Network: Incorporating Multi-stage Visual Cues for Small Organ Segmentation

Qihang Yu;Lingxi Xie;Yan Wang;Yuyin Zhou.
computer vision and pattern recognition (2018)

125 Citations

PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search

Yuhui Xu;Lingxi Xie;Xiaopeng Zhang;Xin Chen.
international conference on learning representations (2020)

113 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 Lingxi Xie

Alan L. Yuille

Alan L. Yuille

Johns Hopkins University

Publications: 118

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 53

Rongrong Ji

Rongrong Ji

Xiamen University

Publications: 26

Baochang Zhang

Baochang Zhang

Beihang University

Publications: 26

Xiangyu Zhang

Xiangyu Zhang

Hong Kong University of Science and Technology

Publications: 24

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 24

Holger R. Roth

Holger R. Roth

Nvidia (United States)

Publications: 20

Bing Xue

Bing Xue

Victoria University of Wellington

Publications: 20

Junjie Yan

Junjie Yan

SenseTime

Publications: 19

Mengjie Zhang

Mengjie Zhang

Victoria University of Wellington

Publications: 19

Yi Yang

Yi Yang

Zhejiang University

Publications: 19

Liang Zheng

Liang Zheng

Australian National University

Publications: 19

Wengang Zhou

Wengang Zhou

University of Science and Technology of China

Publications: 17

Le Lu

Le Lu

PAII Inc.

Publications: 16

Song Bai

Song Bai

ByteDance

Publications: 16

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