نتایج جستجو برای: least squares support vector machine

تعداد نتایج: 1376312  

2014
Kun Zhang Minrui Fei Xin Li Huiyu Zhou

Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images. In order to...

2007
Kai-Ling Mak D. H. Yang

show that the proposed method is an excellent forecasting tool for logistics management.

Journal: :Remote Sensing 2015
Xiya Zhang Peijun Li Cai Cai

Stable night-time light data from the Defense Meteorological Satellite Program (DMSP) Operational Line-scan System (OLS) provide a unique proxy for anthropogenic development. This paper presents a regional urban extent extraction method using a one-class classifier and combinations of DMSP/OLS stable night-time light (NTL) data, MODIS normalized difference vegetation index (NDVI) data, and land...

Journal: :Knowl.-Based Syst. 2015
Divya Tomar Sonali Agarwal

Article history: Received 9 September 2014 Received in revised form 25 January 2015 Accepted 9 February 2015 Available online xxxx

Journal: :Pattern Recognition Letters 2013
Shuo Xu Xin An Xiaodong Qiao Lijun Zhu Lin Li

a Information Technology Supporting Center, Institute of Scientific and Technical Information of China No. 15 Fuxing Rd., Haidian District, Beijing 100038, China b School of Economics and Management, Beijing Forestry University No. 35 Qinghua East Rd., Haidian District, Beijing 100038, China College of Information and Electrical Engineering, China Agricultural University No. 17 Qinghua East Rd....

2001
Tony Van Gestel Johan A. K. Suykens Bart De Moor Joos Vandewalle

Journal: :Engineering Applications of Artificial Intelligence 2019

2013
Ljiljana Zigic Robert Strack Vojislav Kecman

The paper presents a novel learning algorithm for the class of L2 Support Vector Machines classifiers dubbed Direct L2 SVM. The proposed algorithm avoids solving the quadratic programming problem and yet, it produces both the same exact results as the classic quadratic programming based solution in a significantly shorter CPU time. The connections between various L2 SVM algorithms will be highl...

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