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 63 Citations 20,967 363 World Ranking 1288 National Ranking 735

Research.com Recognitions

Awards & Achievements

2002 - SPIE Fellow

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Algorithm

His main research concerns Artificial intelligence, Hyperspectral imaging, Pattern recognition, Image processing and Computer vision. His Artificial intelligence and Contextual image classification, Projection, Endmember, Gaussian noise and Independent component analysis investigations all form part of his Artificial intelligence research activities. His Projection research incorporates themes from Projection pursuit and Least squares.

His research in Hyperspectral imaging intersects with topics in Pixel, Subpixel rendering, Multispectral pattern recognition, Algorithm and Multidimensional signal processing. His Pattern recognition study incorporates themes from Subspace topology, Kullback–Leibler divergence and Signal processing. His Computer vision research is multidisciplinary, relying on both Classifier and Anomaly detection.

His most cited work include:

  • Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection approach (1187 citations)
  • Hyperspectral Imaging: Techniques for Spectral Detection and Classification (846 citations)
  • Estimation of number of spectrally distinct signal sources in hyperspectral imagery (754 citations)

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

His primary scientific interests are in Artificial intelligence, Hyperspectral imaging, Pattern recognition, Computer vision and Algorithm. His Pixel, Image processing, Contextual image classification, Projection and Subpixel rendering investigations are all subjects of Artificial intelligence research. He is involved in the study of Hyperspectral imaging that focuses on Endmember in particular.

Pattern recognition is closely attributed to Spectral signature in his research. When carried out as part of a general Computer vision research project, his work on Image is frequently linked to work in Object detection, therefore connecting diverse disciplines of study. His biological study spans a wide range of topics, including Mathematical optimization and Curse of dimensionality.

He most often published in these fields:

  • Artificial intelligence (69.88%)
  • Hyperspectral imaging (62.25%)
  • Pattern recognition (52.61%)

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

  • Hyperspectral imaging (62.25%)
  • Artificial intelligence (69.88%)
  • Pattern recognition (52.61%)

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

His primary areas of study are Hyperspectral imaging, Artificial intelligence, Pattern recognition, Algorithm and Anomaly detection. His study in Hyperspectral imaging is interdisciplinary in nature, drawing from both Pixel, Image, Sparse matrix and Compressed sensing. His study in the fields of Feature extraction under the domain of Artificial intelligence overlaps with other disciplines such as Object detection.

Chein-I Chang combines subjects such as Spatial analysis and Hyperspectral image classification with his study of Pattern recognition. The various areas that he examines in his Algorithm study include Matrix decomposition, Simplex, Mathematical optimization, Dimensionality reduction and Endmember. His Anomaly detection research is multidisciplinary, incorporating elements of Discriminative model, Anomaly, Constant false alarm rate and Detector.

Between 2015 and 2021, his most popular works were:

  • A Review of Virtual Dimensionality for Hyperspectral Imagery (33 citations)
  • Real-Time Progressive Hyperspectral Image Processing (29 citations)
  • Comparative Study and Analysis Among ATGP, VCA, and SGA for Finding Endmembers in Hyperspectral Imagery (27 citations)

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

  • Artificial intelligence
  • Statistics
  • Algorithm

Chein-I Chang focuses on Hyperspectral imaging, Artificial intelligence, Pattern recognition, Feature extraction and Minimum-variance unbiased estimator. His work deals with themes such as Signal-to-noise ratio, Algorithm, Decorrelation and Real image, which intersect with Hyperspectral imaging. His work in the fields of Artificial intelligence, such as Contextual image classification, overlaps with other areas such as A priori and a posteriori.

His Support vector machine, Classifier and Anomaly detection study in the realm of Pattern recognition interacts with subjects such as Object detection. Chein-I Chang has included themes like Feature, Feature vector, Feature learning, Discriminative model and Robustness in his Feature extraction study. His study focuses on the intersection of Minimum-variance unbiased estimator and fields such as Adaptive beamformer with connections in the field of Covariance matrix, Signal processing and Otsu's method.

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

Hyperspectral Imaging: Techniques for Spectral Detection and Classification

"Chein-I Chang.
(2003)

1899 Citations

Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection approach

J.C. Harsanyi;C.-I. Chang.
IEEE Transactions on Geoscience and Remote Sensing (1994)

1795 Citations

Estimation of number of spectrally distinct signal sources in hyperspectral imagery

Chein-I Chang;Qian Du.
IEEE Transactions on Geoscience and Remote Sensing (2004)

1080 Citations

Hyperspectral Data Exploitation: Theory and Applications

Chein-I Chang.
(2007)

634 Citations

Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis

Jing Wang;Chein-I Chang.
IEEE Transactions on Geoscience and Remote Sensing (2006)

607 Citations

Anomaly detection and classification for hyperspectral imagery

Chein-I Chang;Shao-Shan Chiang.
IEEE Transactions on Geoscience and Remote Sensing (2002)

554 Citations

An information-theoretic approach to spectral variability, similarity, and discrimination for hyperspectral image analysis

Chein-I Chang.
IEEE Transactions on Information Theory (2000)

553 Citations

A New Growing Method for Simplex-Based Endmember Extraction Algorithm

Chein-I Chang;Chao-Cheng Wu;Wei-min Liu;Yen-Chieh Ouyang.
IEEE Transactions on Geoscience and Remote Sensing (2006)

541 Citations

A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification

Chein-I Chang;Qian Du;Tzu-Lung Sun;M.L.G. Althouse.
IEEE Transactions on Geoscience and Remote Sensing (1999)

529 Citations

Hyperspectral Data Processing: Algorithm Design and Analysis

Chein-I Chang.
(2013)

493 Citations

Best Scientists Citing Chein-I Chang

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Qian Du

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Mississippi State University

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Wuhan University

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Nicolas Dobigeon

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Javier Plaza

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Bo Du

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Wuhan University

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Jose M. Bioucas-Dias

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Jean-Yves Tourneret

Jean-Yves Tourneret

Federal University of Toulouse Midi-Pyrénées

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Jocelyn Chanussot

Jocelyn Chanussot

Grenoble Alpes University

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Jun Li

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Sun Yat-sen University

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Jon Atli Benediktsson

Jon Atli Benediktsson

University of Iceland

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Xiuping Jia

Xiuping Jia

UNSW Sydney

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Peijun Du

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Ministry of Natural Resources and Forestry

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Licheng Jiao

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Xidian University

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Lorenzo Bruzzone

Lorenzo Bruzzone

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Zhenwei Shi

Zhenwei Shi

Beihang University

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

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