A
Anirban Mukherjee
Researcher at Indian Institute of Technology Kharagpur
Publications - 97
Citations - 1081
Anirban Mukherjee is an academic researcher from Indian Institute of Technology Kharagpur. The author has contributed to research in topics: Computer science & Support vector machine. The author has an hindex of 13, co-authored 76 publications receiving 822 citations. Previous affiliations of Anirban Mukherjee include Center for Information Technology & Indian Institutes of Technology.
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Journal ArticleDOI
Automatic Defect Detection on Hot-Rolled Flat Steel Products
TL;DR: Test results reveal that three-level Haar feature set is more promising to address the problem of automatic defect detection on hot-rolled steel surface than the other wavelet feature sets as well as texture-based segmentation or thresholding technique of defect detection.
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Nonparallel plane proximal classifier
TL;DR: The formulation of NPPC for binary data classification is based on two identical mean square error (MSE) optimization problems which lead to solving two small systems of linear equations in input space and it eliminates the need of any specialized software for solving the quadratic programming problems (QPPs).
Journal ArticleDOI
Cancer Classification from Gene Expression Data by NPPC Ensemble
TL;DR: A nonparallel plane proximal classifier (NPPC) ensemble that ensures high classification accuracy of test samples in a computer-aided diagnosis (CAD) framework than that of a single NPPC model is presented.
Proceedings ArticleDOI
Media-independent watermarking classification and the need for combining digital video and audio watermarking for media authentication
TL;DR: This paper summarizes the main watermarking parameters and introduces a media independent classification scheme, which is based on the application areas, and addresses the need for combining digital video and audio water marking for media authentication.
Journal ArticleDOI
A novel wavelet neural network based pathological stage detection technique for an oral precancerous condition
Ranjan Rashmi Paul,Anirban Mukherjee,Pranab K. Dutta,Swapna Banerjee,Mousumi Pal,Jyotirmoy Chatterjee,Keya Chaudhuri,K Mukkerjee +7 more
TL;DR: The results obtained from this proposed technique were promising and suggest that with further optimisation this method could be used to detect and stage OSF, and could be adapted for other conditions.