A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching-Reference-Cited by-同舟云学术

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A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching

Published:2024-09 Issue:9 Volume:59 Page:3070-3081
ISSN:0018-9200
Container-title:IEEE Journal of Solid-State Circuits
language:
Short-container-title:IEEE J. Solid-State Circuits

Author:

Feng Xiaoyu¹^ORCID,Sun Wenyu¹^ORCID,Tang Chen¹^ORCID,Lin Xinyuan¹^ORCID,Yue Jinshan²^ORCID,Yang Huazhong¹^ORCID,Liu Yongpan¹^ORCID

Affiliation:

1. Department of Electronic Engineering, Tsinghua University, Beijing, China

2. Institute of Microelectronics, Chinese Academy of Sciences, Beijing, China

Funder

National Key Research and Development Program

Strategic Priority Research Program of Chinese Academy of Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4/10648889/10508796.pdf?arnumber=10508796

Reference36 articles.

1. SECOND: Sparsely Embedded Convolutional Detection

2. PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection

3. LiDAR R-CNN: An Efficient and Universal 3D Object Detector

4. SEFormer: Structure Embedding Transformer for 3D Object Detection

5. Embracing Single Stride 3D Object Detector with Sparse Transformer

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