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Persoonlijk profiel

Research profile

Narsimlu Kemsaram is a Postdoctoral Researcher with the Video Coding and Architectures (VCA) Research Group, Mobile Perception Systems (MPS) Research Lab at the Eindhoven University of Technology (TU/e), Eindhoven, Netherlands. He is currently working in the i-CAVE (integrated Cooperative Automated Vehicles) P1 Sensing, Mapping, and Localization project. He has worked in various Aerospace & Defence industries. Key research areas: Autonomous Vehicles, Computer Vision, Deep Learning, and Artificial Intelligence.

Academic background

Narsimlu Kemsaram received his Doctor of Philosophy (Ph.D.) degree in Computer Science and Engineering from the Jawaharlal Nehru Technological University (JNT University), Hyderabad, India, on the topic of "Design and Development of Autonomous Visual Tracking Algorithm for Unmanned Aerial Vehicles". He received his Master of Business Administration (MBA) degree in Aerospace from the Toulouse Business School, Toulouse, France (TBS France) and from the Indian Institute of Management, Bangalore (IIM Bangalore), India including international modules in the Toulouse (France), Bangalore (India), Seattle (USA), Brussels (Belgium). He received his Master of Technology (M.Tech) degree in Computer Science from the Jawaharlal Nehru Technological University (JNT University), Hyderabad, India. He received his Bachelor of Technology (B.Tech) degree in Computer Science and Engineering from the National Institute of Technology, Warangal (NIT Warangal), India.

Opleiding / Academische kwalificatie

Bachelor, National Institute of Technology Warangal

Master, Indian Institute of Management Bangalore

Master, Jawaharlal Nehru Technological University

Doctor, Jawaharlal Nehru Technological University

Master, Toulouse Business School

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Onderzoeksoutput

  • 2 Citaties
  • 10 Tijdschriftartikel
  • 3 Conferentiebijdrage

An integrated framework for autonomous driving: object detection, lane detection, and free space detection

Kemsaram, N., Das, A. & Dubbelman, G., 31 jul 2019, 2019 Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4). Yang, X-S., Dey, N. & Joshi, A. (redactie). Piscataway: Institute of Electrical and Electronics Engineers, blz. 260-265 6 blz. 8904020

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Open Access
  • 2 Downloads (Pure)

    A multi-level visual tracking algorithm for autonomous vehicles

    Kemsaram, N., Rajini Kanth, T. V., Guntupalli, D. R. & Kuvvarapu, A., aug 2017, In : International Journal of Advanced Research in Computer Science. 8, 7, blz. 1156-1162 7 blz.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    Open Access
    Bestand
  • 18 Downloads (Pure)

    Design and development of an on-board autonomous visual tracking system for unmanned aerial vehicles

    Kemsaram, N., Rajini Kanth, T. V., Guntupalli, D. R. & Kuvvarapu, A., 8 sep 2017, In : Aviation. 21, 3, blz. 83-91 9 blz.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

  • 1 Citaat (Scopus)

    Autonomous visual tracking with Extended Kalman Filter estimator for micro aerial vehicles

    Kemsaram, N., Rajini Kanth, T. V. & Guntupalli, D. R., 1 dec 2015, Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing-2015 (FANCCO-2015). Suganthan, P. N., Ravi, V., Das, S. & Panigrahi, B. K. (redactie). Berlin: Springer, blz. 31-42 12 blz. (Advances in Intelligent Systems and Computing; vol. 415).

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

  • 1 Citaat (Scopus)

    An experimental study of the autonomous visual target tracking algorithms for small unmanned aerial vehicles

    Kemsaram, N., Rajini Kanth, T. V. & Guntupalli, D. R., nov 2014, 1st International Conference on Rough Sets and Knowledge Technologies-2014 (ICRSKT-2014). Elsevier, blz. 52-59 8 blz.

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review