A Real-time 17-Scale Object Detection Accelerator with Adaptive 2000-Stage Classification in 65nm CMOS

被引：0

作者：

Kim, Minkyu ^{[1
]}

Mohanty, Abinash ^{[1
]}

Kadetotad, Deepak ^{[1
]}

Suda, Naveen ^{[3
]}

Wei, Luning ^{[2
]}

Saseendran, Pooja ^{[1
]}

He, Xiaofei ^{[2
]}

Cao, Yu ^{[1
]}

Seo, Jae-sun ^{[1
]}

机构：

[1] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ 85281 USA

[2] Zhejiang Univ, Coll Comp Sci, Hangzhou, Zhejiang, Peoples R China

[3] ARM Inc, San Jose, CA USA

来源：

2017 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2017年

关键词：

object detection; machine learning; classification; real-time; low-power; special-purpose accelerator;

D O I：

暂无

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：

This paper presents an object detection accelerator that features many-scale (17), many-object (up to 50), multi-class (e.g., face, traffic sign), and high accuracy (average precision of 0.79/0.65 for AFW/BTSD datasets). Employing 10 gradient/color channels, integral features are extracted, and the results of 2,000 simple classifiers for rigid boosted templates are adaptively combined to make a strong classification. By jointly optimizing the algorithm and the hardware architecture, the prototype chip implemented in 65nm CMOS demonstrates real-time object detection of 13-35 frames per second with low power consumption of 22-160mW at 0.58-1.0V supply.

引用

页码：2038 / 2041

页数：4

共 10 条

[1] A Real-time 17-Scale Object Detection Accelerator with Adaptive 2000-Stage Classification in 65nm CMOS
Kim, Minkyu
Mohanty, Abinash
Kadetotad, Deepak
Suda, Naveen
Wei, Luning
Saseendran, Pooja
He, Xiaofei
Cao, Yu
Seo, Jae-Sun
[J]. 2017 22ND ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE (ASP-DAC), 2017, : 21 - 22
[2] A Real-Time 17-Scale Object Detection Accelerator With Adaptive 2000-Stage Classification in 65 nm CMOS
Kim, Minkyu
Mohanty, Abinash
Kadetotad, Deepak
Wei, Luning
He, Xiaofei
Cao, Yu
Seo, Jae-Sun
[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2019, 66 (10) : 3843 - 3853
[3] Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS
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[J]. 2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2018,
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[J]. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2020, 20 (06): : 216 - 222
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[J]. PROCEEDINGS OF THE 2020 57TH ACM/EDAC/IEEE DESIGN AUTOMATION CONFERENCE (DAC), 2020,
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[8] Adaptive Scale and Correlative Attention PointPillars: An Efficient Real-Time 3D Point Cloud Object Detection Algorithm
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[J]. APPLIED SCIENCES-BASEL, 2024, 14 (09):
[9] YoloOW: A Spatial Scale Adaptive Real-Time Object Detection Neural Network for Open Water Search and Rescue From UAV Aerial Imagery
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[10] A 50MHz 5V 3W 90% Efficiency 3-Level Buck Converter with Real-Time Calibration and Wide Output Range for Fast-DVS in 65nm CMOS
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