Dr. Akansha Tyagi

About

I am Dr. Akansha Tyagi, received Ph.D. degree from Maharishi Markandeswar (deemed to be) University, Mullana, Ambala, Haryana under the supervision of Dr. Sandhya Bansal-Professor at Maharishi Markandeswar (deemed to be) University, Mullana, Ambala, Haryana. My Ph.D. thesis title was “An Efficient System for Vision-Based Recognition of Indian Sign Language Using Soft-Computing Techniques”. I completed my M. Tech from Maharishi Dayanand University Rohtak, (Haryana) and B. Tech from Punjab Technical University (Punjab). My areas of interest are Soft-computing, Sign language recognition, and computer vision. I have three years of teaching experience. The last position I served was as an Assistant Professor in Chandigarh University from duration Mar-2022 to May-2022. Currently working as an Assistant Professor in BVRITH Women’s Engineering College, Hyderabad.

Employment

• BVRIT Hyderabad College of Engineering For Women Assistant Professor
  2023 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (11)

• Advancements in hemotype identification: Fingerprint analysis for blood group determination
  Franklin Open 2025 DOI: 10.1016/j.fraope.2025.100429
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• Real-time sign language gesture recognition for Women's safety using dynamic time warping and voting algorithms
  Franklin Open 2025 DOI: 10.1016/j.fraope.2025.100428
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• Hand Anatomy and Neural Network-Based Recognition for Sign Language
  IETE Journal of Research 2024 DOI: 10.1080/03772063.2023.2171911
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• Hand Anatomy and Neural Network Based Recognition of Isolated and Real-Life Words of Indian Sign Language
  Proceedings in Adaptation, Learning and Optimization 2023 DOI: 10.1007/978-3-031-31164-2_17
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• Recognition of Indian Sign Language using Hand geometry and Neural Network
  2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) 2022 DOI: 10.1109/icccis56430.2022.10037642
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• Hand Anatomy and Neural Network Based Recognition for Sign Language
  2022 DOI: 10.2139/ssrn.4172019
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• Hybrid FiST_CNN Approach for Feature Extraction for Vision-Based Indian Sign Language Recognition
  International Arab Journal of Information Technology 2022 DOI: 10.34028/IAJIT/19/3/15
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• Sign Language Recognition Using Hand Mark Analysis for Vision-Based System (HMASL)
  Lecture Notes in Electrical Engineering 2022 DOI: 10.1007/978-981-16-8774-7_35
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• Comparative Analysis of Feature Detection and Extraction Techniques for Vision-based ISLR system
  2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC) 2020
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• Feature Extraction Technique for Vision-Based Indian Sign Language Recognition System: A Review
  Advances in Soft Computing 2020 DOI: 10.1007/978-981-15-6876-3_4
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