P
Pavan Chakraborty
Researcher at Indian Institute of Information Technology, Allahabad
Publications - 81
Citations - 1195
Pavan Chakraborty is an academic researcher from Indian Institute of Information Technology, Allahabad. The author has contributed to research in topics: Gait (human) & Robot. The author has an hindex of 17, co-authored 78 publications receiving 948 citations. Previous affiliations of Pavan Chakraborty include Indian Institute of Astrophysics & Inter-University Centre for Astronomy and Astrophysics.
Papers
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Journal ArticleDOI
Local directional gradient pattern: a local descriptor for face recognition
TL;DR: The proposed descriptor considerably reduces the length of the micropattern which consequently reduces the extraction time and matching time while maintaining the recognition rate, and is more resistant against the AWGN compared to the other state of the art descriptors used for face recognition problems.
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Local Gradient Hexa Pattern: A Descriptor for Face Recognition and Retrieval
TL;DR: A local gradient hexa pattern is proposed that identifies the relationship among the reference pixel and its neighboring pixels at different distances across different derivative directions, effectively transforming these relationships into binary micropatterns discriminating inter-class facial images with optimal precision.
Book ChapterDOI
Recognition of Isolated Indian Sign Language Gesture in Real Time
TL;DR: Indian Sign Language (ISL) consists of static as well as dynamic hand gestures for communication among deaf and dumb persons and two different approaches utilized for recognition are Euclidean distance and K-nearest neighbor metrics.
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Less computationally intensive fuzzy logic (type-1)-based controller for humanoid push recovery
TL;DR: The novel feature of this study is the introduction of an intuitive fuzzy logic-based learning approach that is fast and effective and extends the Gordon model for balancing humanoids by considering the effects of roll, pitch, and yaw.
Journal ArticleDOI
DeepLNC, a long non-coding RNA prediction tool using deep neural network
TL;DR: The proposed classifier, Deep Neural Network (DNN) is fast and an accurate alternative for the identification of lncRNAs as compared to other existing classifiers and k-mer information content generated on the basis of Shannon entropy function has resulted in improved classifier accuracy.