December 2018
DEC
20
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MIKE 2018 is an interdisciplinary conference that brings together researchers and practitioners from the domains of lear...
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Cluj-Napoca, |
February 2019
FEB
22
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Paper Publication: All accepted papers must be written in English and will be published into #ACM Conference Proceeding...
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Zhuhai, |
September 2019
SEP
20
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Lexis invites all the participants across the globe to attend the International conference on Artificial Intelligence du...
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Vancouver, |
October 2019
OCT
18
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Conference official website:http://www.rsvt.org/ Meeting time:October 18-20, 2019. Meeting place:Wuhan, China. ...
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Wuhan, |
November 2019
NOV
19
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[Scopus/Ei Compendex] 2019 International Conference on Machine Learning and Intelligent Systems (MLIS 2019) Website: ...
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, |
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NOV
27
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Conference official website:http://www.spml.net Meeting time:November 27-29, 2019. Meeting place:Hangzhou, China...
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Hangzhou, |
June 2020
JUN
18
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The Robot Intelligence Technology & Applications Webinar (iRobot-2020) is the only 100% inclusive, 100% virtual event de...
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JUN
20
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International Conference on Machine learning and Cloud Computing (MLCL 2020) June 20~21, 2020, Dubai, UAE https://csit...
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, |
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JUN
25
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In this modern world of computer science, researchers focus mainly on the integration of Artificial Intelligence and oth...
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Secunderabad, |
July 2020
JUL
20
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3rd International Conference on Computer Science & Cloud Computing (Cloud Science-2020), which will be held during July ...
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Montreal, |
August 2020
AUG
13
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The 6th International Conference on Machine Vision and Machine Learning (MVML’20) aims to become the leading annual co...
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September 2020
SEP
10
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In this 2-day training, you will learn how to build machine learning applications in C# with Microsoft’s new ML.NET li...
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, |
October 2020
OCT
19
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Join the machine learning revolution. O'Reilly TensorFlow World brings together the vibrant and growing ecosystem that'...
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Santa Clara, |
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OCT
24
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International Conference on Machine Learning Techniques and NLP (MLNLP 2020) October 24-25, 2020, Sydney, Australia...
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, |
January 2021
JAN
23
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2nd International Conference on Signal Processing and Machine Learning (SIGML 2021) January 23~24, 2021, Zurich, Swit...
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Zurich, |
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JAN
23
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8th International Conference on Bioinformatics and Bioscience (ICBB 2021) January 23~24, 2021, Zurich, Switzerland http...
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Zurich, |
February 2021
FEB
4
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10th International Conference on Pattern Recognition Applications and Methods ICPRAM website: http://www.icpram.org ...
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Vienna, |
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FEB
8
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Intellipaat’s Machine Learning online course in Bangalore will help you be a master in the concepts and techniques of ...
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Bangalore, |
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FEB
26
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Publication: All submitted papers will be sent to 2-3 peer reviewers for review. And accepted and presented papers wi...
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Shenzhen, |
March 2021
MAR
27
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2nd International Conference on Natural Language Processing and Machine Learning (NLPML 2021) March 27 ~ 28, 2021, Sydn...
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, |
April 2021
APR
14
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International Journal of Computer Science & Information Technology (IJCSIT) ISSN: 0975-3826(online); 0975-4660 (Prin...
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, |
June 2021
JUN
10
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Publication: The accepted paper will be included into ICSLT 2021 Conference Proceedings, which will be published in t...
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Portsmouth, |
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JUN
25
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3rd International Conference on New Approaches in Education, which will be held in Oxford, UK during 25-27 June, 2021. ...
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oxford, |
July 2021
JUL
16
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The 4th Int'l Conference on Machine Learning, Pattern Recognition and Intelligent Systems (MLPRIS 2021) Conference Date...
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Kunming, |
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JUL
29
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The 7th International Conference on Machine Vision and Machine Learning (MVML’21) aims to become the leading annual co...
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August 2021
AUG
18
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Accepted papers will be published in the Conference Proceedings by ACM, which will be indexed by EI Compendex, Scopus, a...
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Beijing, |
October 2021
OCT
23
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2nd International Conference on Data Science and Machine Learning (DSML 2021) October 23 ~ 24, 2021, Sydney, Australia ...
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Sydney, Australia, |
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06/26/2017 |
The purpose of this thesis is to forecast the amount of network traffic in Transmission Control Protocol/Internet Protocol (TCP/IP) -based networks by using different time lags and various machine learning methods including Support Vector Machines (SVM), Multilayer Perceptron (MLP), Radial Basis Function (RBF) Neural Network, M5P (a decision tree with linear regression functions at the nodes), Random Forest (RF), Random Tree (RT), and Reduced Error Prunning Error (REPTree), and statistical regression methods including Multiple Linear Regression (MLR) and Holt-Winters and compare the performance of statistical and machine learning methods. Two different Internet Service Providers' (ISPs) traffic data have been utilized to build traffic forecasting models. The first 66% of the data sets has ... |
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03/02/2017 |
Upper body power (UBP) is one of the most important factors affecting the performance of cross-country skiers during races. Although some initial studies have already attempted to predict UBP, until now, no study has attempted to apply machine learning methods combined with various feature selection algorithms to identify the discriminative features for prediction of UBP. The purpose of this study is to develop new prediction models for predicting the 10-second UBP (UBP10) and 60-second UBP (UBP60) of cross-country skiers by using General Regression Neural Networks (GRNN), Radial-Basis Function Network (RBF), Multilayer Perceptron (MLP), Support Vector Machine (SVM), Single Decision Tree (SDT) and Tree Boost (TB) along with the Relief-F feature selection algorithm, minimum redundancy maxim... |
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06/28/2017 |
The purpose of this thesis is to develop new hybrid admission decision prediction models by using different machine learning methods including Support Vector Machines (SVM), Multilayer Perceptron (MLP), Radial Basis Function (RBF) Network, TreeBoost (TB) and K-Means Clustering (KMC) combined with feature selection algorithms to investigate the effect of the predictor variables on the admission decision of a candidate to the School of Physical Education and Sports at Cukurova University. Three feature selection algorithms including Relief-F, F-Score and Correlation-based Feature Selection (CFS) have been considered. Experiments have been conducted on the datasets, which contain data of participants who applied to the School in 2006 and 2007. The datasets have been randomly split into train... |
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Pattern Recognition Methods for Crop Classification from Hyperspectral Remote Sensing Images
Metodos de Clasificacion Aplicados al Reconocimiento de Campos de Cultivo a partir de Imagenes Hiperespectrales 05/21/2004 |
(Complete work in Spanish) Remote sensing aerial spectral imaging was one of the first application areas where spectral imaging was used in order to identify and monitor the natural resources and covers on earth surface. Aerial spectral imaging is being developed with the aim of monitoring natural resources like coastal areas, forestry and extensive crops. The information contained in hyperspectral images allows the reconstruction of the energy curve radiated by the terrestrial surface throughout the electromagnetic spectrum. Hence, the characterization, identification and classification of the observed material from their spectral curve is an interesting possibility. Pattern recognition methods have proven to be effective techniques in this kind of applications. In fact, classification of... |