Object detection for infrared ground to ground applications on the edge

Abhijit Bhattacharjee; Birju Patel; Alexander J. Taylor; Joseph A. Rivera

doi:10.1117/12.3012659

7 June 2024 Object detection for infrared ground to ground applications on the edge

Abhijit Bhattacharjee, Birju Patel, Alexander J. Taylor, Joseph A. Rivera

Proceedings Volume 13039, Automatic Target Recognition XXXIV; 130390M (2024) https://doi.org/10.1117/12.3012659
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

We present a streamlined pipeline that generates a YOLO object detection application using MATLAB software and NVIDIA^® hardware. The application utilizes MATLAB GPU Coder and NVIDIA^® TensorRT^™ to accelerate inferencing on NVIDIA processors, specifically the latest Jetson Orin^™ embedded processor. We evaluated the object detector on the open U.S. Army Automated Target Recognition (ATR) Development Image Dataset (ADID) for multi-class vehicle detection and classification. Overall, this workflow decreases development time over traditional approaches and provides a quick route to low-code deployment on the latest NVIDIA Jetson Orin. This work offers value to researchers and practitioners in many application areas aiming to harness the power of NVIDIA processors for rapid, efficient object detection solutions.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Abhijit Bhattacharjee, Birju Patel, Alexander J. Taylor, and Joseph A. Rivera "Object detection for infrared ground to ground applications on the edge", Proc. SPIE 13039, Automatic Target Recognition XXXIV, 130390M (7 June 2024); https://doi.org/10.1117/12.3012659

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KEYWORDS

Object detection

Education and training

Sensors

MATLAB

Army

Detection and tracking algorithms

Infrared radiation

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