A real-time learning processor based on K-means algorithm with automatic seeds generation

被引：0

作者：

Shikano, Hirotsugu ^{[1
]}

Ito, Kiyoto ^{[1
]}

Fujita, Kazuhide ^{[1
]}

Shibata, Tadashi ^{[1
]}

机构：

[1] Univ Tokyo, Dept Frontier Informat, Tokyo, Japan

来源：

2007 INTERNATIONAL SYMPOSIUM ON SYSTEM-ON-CHIP PROCEEDINGS | 2007年

关键词：

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：

A full-custom learning processor architecture has been developed based on the K-means algorithm aiming at real-time clustering applications. In order to accelerate the convergence and improve the quality of solutions, an automatic initial seeds generation function has been implemented in the architecture. The concept has been verified by the measurement of the proof-of-concept chip designed and fabricated in a 0.18-mu m 5-metal CMOS technology. A full custom chip was also designed using the same technology and sent to fabrication and its operation was confirmed by simulation.

引用

页码：7 / 10

页数：4

共 50 条

[1] K-MEANS BASED SEGMENTATION FOR REAL-TIME ZENITHAL PEOPLE COUNTING
Antic, Borislav
Letic, Dragan
Culibrk, Dubravko
Crnojevic, Vladimir
2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 2009, : 2565 - 2568
[2] K-means Based Transfer Learning Algorithm
Du, Yuanyuan
Li, Bo
Quan, Zhonghua
ADVANCED INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS, ICIC 2023, PT IV, 2023, 14089 : 179 - 190
[3] Application of K-Means Clustering Algorithm in Automatic Machine Learning
Ji, Dongri (jidongri0016@163.com), 1600, Springer Science and Business Media Deutschland GmbH (1131):
[4] Real-time segmentation of color images based on the k-means clustering on FPGA
Saegusa, Takashi
Maruyama, Tsutomu
ICFPT 2007: INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE TECHNOLOGY, PROCEEDINGS, 2007, : 329 - 332
[5] Real-Time Forecast of Tourists Distribution Based on the Improved k-Means Method
Ren, Peiyu
Liao, Zhixue
Ge, Peng
MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
[6] Implementation of Real-Time Skin Segmentation Based on K-Means Clustering Method
De, Souranil
Rakshit, Soumik
Biswas, Abhik
Saha, Srinjoy
Datta, Sujoy
COMPUTATIONAL VISION AND BIO-INSPIRED COMPUTING, 2020, 1108 : 964 - 973
[7] A low complexity hardware architecture of K-means algorithm for real-time satellite image segmentation
Rahul Ratnakumar
Satyasai Jagannath Nanda
Multimedia Tools and Applications, 2019, 78 : 11949 - 11981
[8] A low complexity hardware architecture of K-means algorithm for real-time satellite image segmentation
Ratnakumar, Rahul
Nanda, Satyasai Jagannath
MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (09) : 11949 - 11981
[9] A Novel Hybrid Algorithm Based on K-Means and Evolutionary Computations for Real Time Clustering
Mansouri, Taha
Ravasan, Ahad Zare
Gholamian, Mohammad Reza
INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING, 2014, 10 (03) : 1 - 14
[10] Evaluation of an Optimized K-Means Algorithm Based on Real Data
Poteras, Cosmin M.
Mocanu, Mihai L.
PROCEEDINGS OF THE 2016 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 2016, 8 : 831 - 835

← 1 2 3 4 5 →