AK
ANISH MONSLEY KIRUPAKARAN
Also known as: Anish Monsley K.
FedEx SMART Center for Supply Chain Modeling, Algorithms, Research & Technology, IIT Madras, Indian Institute of Technology Madras, National Institute Of Technology Silchar
Employment
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FedEx SMART Center for Supply Chain Modeling, Algorithms, Research & Technology, IIT Madras Senior Project Officer2025 - Present
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Indian Institute of Technology Madras Senior Project Officer2022 - 2025
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Indian Institute of Technology Madras Senior Research Fellow2022 - 2022
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National Institute of Technology Silchar Senior Research Fellow2021 - 2022
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National Institute of Technology Silchar Junior Research Fellow2019 - 2021
Education
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National Institute Of Technology Silchar Doctor of Philosophy2019 - 2023
Projects & Funding
Projects & funding information is unavailable.
Publications (13)
- A coherent framework for simultaneous detection and spotting of the nucleus phase from the mid-air gesticulation of alphanumeric keys Save
- Development of an intelligent recognition system for dynamic mid-air gesticulation of isolated alphanumeric keys Save
- Resolving the ambiguity in recognizing case-sensitive characters gesticulated in mid-air through post-decision support modules Save
- Exploration of Deep Convolutional Neural Networks(Via Transfer Learning) for Handwritten Character Recognition Save
- Design and development of a vision‐based system for detection, tracking and recognition of isolated dynamic bare hand gesticulated characters Save
- Self Co-articulation Removal in Mid-air Gesticulated Trajectories via a Sequence-to-Sequence Based Classification Approach using LSTM Save
- A selective region-based detection and tracking approach towards the recognition of dynamic bare hand gesture using deep neural network Save
- Genetic algorithm based optimized watermarking technique using hybrid DCNN-SVR and statistical approach for watermark extraction Save
- Gesture objects detection and tracking for virtual text entry keyboard interface Save
- Removal of self co-articulation and recognition of dynamic hand gestures using deep architectures Save