Deploying AI Object Detection, Target Tracking, and Computational Imaging Algorithms on Embedded Processors

被引：0
|
作者：
Stout, Art [1 ]
Madineni, Kedar [1 ]
机构：
[1] Teledyne FLIR, 6769 Hollister Ave, Goleta, CA 93117 USA
来源：
INFRARED TECHNOLOGY AND APPLICATIONS L | 2024年 / 13046卷
关键词：
ATR; Classifier; Object Detector; Object Tracking; CNN; Neural Network; System on Chip; SoC; System on Module; SoM; AI; Computational Imaging;
D O I：
10.1117/12.3014180
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The rapid advances in deep learning AI techniques for digital vision-based perception and gains in computational imaging for image quality have converged with innovations in mobile processors and device support to bring very large computing power to the edge. This convergence is creating opportunities for electro-optical systems to become intelligent at the edge and to eliminate issues with latency, compression artifacts, datalink bandwidth, thermal management, and system complexity. We describe the state of the art in embedded processors and the integration of Teledyne FLIR's Prism (TM) thermal and multispectral image signal processing and object detector and tracking libraries into today's most widely deployed embedded platforms.
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页数：13
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