D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 65 Citations 16,301 267 World Ranking 1165 National Ranking 684

Research.com Recognitions

Awards & Achievements

2016 - IAPR P. Zamperoni Award Content Selection Using Frontalness of Multiple Frames

2014 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to the field of document image analysis and in recognition of service to the IAPR

2014 - IEEE Fellow For contributions to research and development of automatic analysis and processing of document page imaging

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

David Doermann mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Search engine indexing. His Artificial intelligence study frequently draws connections to adjacent fields such as Machine learning. David Doermann has researched Computer vision in several fields, including Tree and Perspective.

David Doermann has included themes like Image quality and Inference in his Pattern recognition study. His research in Image quality intersects with topics in Codebook, Distortion and Feature learning. His research in Image processing tackles topics such as Text processing which are related to areas like Motion estimation and Digital video.

His most cited work include:

  • Automatic text detection and tracking in digital video (553 citations)
  • Convolutional Neural Networks for No-Reference Image Quality Assessment (536 citations)
  • Text Detection and Recognition in Imagery: A Survey (500 citations)

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

David Doermann focuses on Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Information retrieval. His Artificial intelligence research includes themes of Machine learning and Natural language processing. His work carried out in the field of Pattern recognition brings together such families of science as Contextual image classification and Handwriting.

The various areas that he examines in his Feature extraction study include Image quality, Codebook and Feature. His Information retrieval study integrates concerns from other disciplines, such as Document clustering and Image retrieval. He interconnects Backpropagation and Deep learning in the investigation of issues within Convolutional neural network.

He most often published in these fields:

  • Artificial intelligence (72.10%)
  • Pattern recognition (36.05%)
  • Computer vision (27.90%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (72.10%)
  • Convolutional neural network (7.52%)
  • Pattern recognition (36.05%)

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

His primary scientific interests are in Artificial intelligence, Convolutional neural network, Pattern recognition, Artificial neural network and Deep learning. His study in the field of Feature and Feature extraction is also linked to topics like Differentiable function. His research integrates issues of Object, Object detection, Backpropagation and Filter in his study of Convolutional neural network.

His Pattern recognition study focuses on Segmentation in particular. The various areas that he examines in his Artificial neural network study include Complex system and Generalizability theory. His study explores the link between Layer and topics such as Event recognition that cross with problems in Computer vision.

Between 2015 and 2021, his most popular works were:

  • Blind Image Quality Assessment Based on High Order Statistics Aggregation (160 citations)
  • Towards Optimal Structured CNN Pruning via Generative Adversarial Learning (117 citations)
  • Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks (87 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

His primary areas of study are Artificial intelligence, Pattern recognition, Convolutional neural network, Deep learning and Feature. Artificial intelligence is closely attributed to Task analysis in his work. In his research on the topic of Pattern recognition, Variation is strongly related with Image.

His Convolutional neural network research is multidisciplinary, relying on both Backpropagation and Filter. His work carried out in the field of Deep learning brings together such families of science as Algorithm and Entropy. His research in Feature intersects with topics in Image quality, Codebook, Data mining, Metric and Density estimation.

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.

Best Publications

Automatic text detection and tracking in digital video

Huiping Li;D. Doermann;O. Kia.
IEEE Transactions on Image Processing (2000)

901 Citations

Convolutional Neural Networks for No-Reference Image Quality Assessment

Le Kang;Peng Ye;Yi Li;David Doermann.
computer vision and pattern recognition (2014)

681 Citations

Text Detection and Recognition in Imagery: A Survey

Qixiang Ye;David Doermann.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2015)

649 Citations

Camera-based analysis of text and documents: a survey

Jian Liang;David Doermann;Huiping Li.
International Journal on Document Analysis and Recognition (2005)

629 Citations

Unsupervised feature learning framework for no-reference image quality assessment

Peng Ye;Jayant Kumar;Le Kang;David Doermann.
computer vision and pattern recognition (2012)

541 Citations

The Indexing and Retrieval of Document Images

David Doermann.
Computer Vision and Image Understanding (1998)

434 Citations

Video summarization by curve simplification

Daniel DeMenthon;Vikrant Kobla;David Doermann.
acm multimedia (1998)

408 Citations

Progress in camera-based document image analysis

D. Doermann;Jian Liang;Huiping Li.
international conference on document analysis and recognition (2003)

391 Citations

Robust point matching for nonrigid shapes by preserving local neighborhood structures

Yefeng Zheng;D. Doermann.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

358 Citations

No-Reference Image Quality Assessment Using Visual Codebooks

Peng Ye;D. Doermann.
IEEE Transactions on Image Processing (2012)

282 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing David Doermann

Chew Lim Tan

Chew Lim Tan

National University of Singapore

Publications: 87

Palaiahnakote Shivakumara

Palaiahnakote Shivakumara

University of Malaya

Publications: 78

Umapada Pal

Umapada Pal

Indian Statistical Institute

Publications: 78

Jonathan J. Hull

Jonathan J. Hull

Independent Scientist / Consultant, US

Publications: 73

Berna Erol

Berna Erol

Ricoh (Japan)

Publications: 45

Weisi Lin

Weisi Lin

Nanyang Technological University

Publications: 42

Alan C. Bovik

Alan C. Bovik

The University of Texas at Austin

Publications: 42

Jamey Graham

Jamey Graham

Ricoh (Japan)

Publications: 38

Michael Blumenstein

Michael Blumenstein

University of Technology Sydney

Publications: 37

Cheng-Lin Liu

Cheng-Lin Liu

Chinese Academy of Sciences

Publications: 34

Venu Govindaraju

Venu Govindaraju

University at Buffalo, State University of New York

Publications: 32

Martin T. King

Martin T. King

Google (United States)

Publications: 28

Faisal Shafait

Faisal Shafait

University of the Sciences

Publications: 28

Xiang Bai

Xiang Bai

Huazhong University of Science and Technology

Publications: 28

Bidyut B. Chaudhuri

Bidyut B. Chaudhuri

Indian Statistical Institute

Publications: 25

Daniel P. Lopresti

Daniel P. Lopresti

Lehigh University

Publications: 24

Something went wrong. Please try again later.