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 language | English |
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Title of host publication | Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 67-68 |
Number of pages | 2 |
ISBN (Electronic) | 9781665470506 |
DOIs | |
State | Published - 2022 |
Externally published | Yes |
Event | 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan Duration: 06 07 2022 → 08 07 2022 |
Publication series
Name | Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 |
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Conference
Conference | 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 |
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Country/Territory | Taiwan |
City | Taipei |
Period | 06/07/22 → 08/07/22 |
Bibliographical note
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