Object Detection Inference System with Deep Learning NVDLA Accelerator

Yeong Kang Lai, Chuan Wei Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays, when Artificial Intelligence (AI) is getting more advanced, many applications are following its footsteps. For example, in the fields of object recognition and speech processing, there are many different DNN (deep neural network) structures. By combining these DNNs and collecting a large library of images or audio. It uses GPUs for training to achieve high accuracy and meet its application requirements. This paper focuses on object recognition in store applications and uses DNN hardware accelerators for real-time inference. It maps to NVDLA hardware using YOLOv2-tiny. NVDLA can perform YOLOv2-tiny with 256 MAC@150 MHz frequency. Also, it can reach up to 5 FPS.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-68
Number of pages2
ISBN (Electronic)9781665470506
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan
Duration: 06 07 202208 07 2022

Publication series

NameProceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Conference

Conference2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Country/TerritoryTaiwan
CityTaipei
Period06/07/2208/07/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

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