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1 2016 Future University Hakodate 2016 System Information Science Practice Group Report AI Project Name AI Love Deep Learning AI Group Name AI Scope /Project No. 14-A /Project Leader Daichi Fukuda /Group Leader Masane Nojiri /Group Member Masane Nojiri Daichi Fukuda Naoki Saito Saito Suzuki Junki Itagaki Advisor Takashi Takenouchi Kiyohito Nagano Kengo Terasawa Yasuhiro Katagiri Date of Submission January 18, 2017
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3 Abstract Recently, artificial intelligence that is able to imitate human in various example appears. Artificial intelligence is a technique which try to realize intelligence just like learning ability human do naturally using machine learning. Deep learning is a technique which produces an excellent result in a field of image processing. The goal of this project is to imitate and transcend human s thinking using these techniques of machine learning. We discuss goal and divide this project into group A and group B. Group A targets development of system of anticipation of pitch. Group B targets development agent of car that is able to drive faster than human s operation. The reason why we chose anticipation of pitch includes populality of baseball in Japan declines from decreasing of program rating of TV itself. In addition, it is said that attendance is decreasing slightly from 2010[2] and increase of popularity of sports other then baseball. So, we want to increase the number of people who have an interest in baseball by producing contents involved baseball. Now, this group focuses Nomura s Scope that is indicated sometimes when Katsuya Nomura who was former professional baseball player expounds baseball in terrestrial broadcasting and we devise implementation of contents like it. To be specific, we are approaching making contents of anticipating of pitch just like Nomura s Scope using machine learning based on player s data of each baseball teams. Additionaly, we divide us into two groups such as, Group of collecting data Making program that extracts data of player from website using Python Group of implemention Making program that implements machine learning using Python We were working in each group in the first semester. Data collection team made a data collection program, and implementation team made the expected program using SVM. In addition, we reviewed implement method and using data for the second semester after the interim presentation. We were working while using collected data in addition to working at each group. Data collection team improved versatility to increase type of collecting data, and enable to take designated data. Implement team promoted making and implemented program of anticipation of pitch using Deep Learning. In addition, we made presentation materials for final presentation at the same time. Keyword Baseball, Machine learning, Anticipating of pitch, Python - ii -
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2015 Future University Hakodate 2015 System Information Science Practice Group Report Project Name Improvement of Environment for Learning Mathematics at FUN C (PR ) Group Name GroupC (PR) /Project No.
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2017 Future University Hakodate 2017 System Information Science Practice Group Report Project Name Manga engineering Group Name Literacy Manga /Project No. 19 /Project Leader 1015131 Kiyomasa Murakami
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2015 Future University Hakodate 2015 System Information Science Practice Group Report Twitter Project Name Twitter Localization Group Name Search Group /Project No. 19 /Project Leader 1013039 Hirohito
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2015 Future University Hakodate 2015 System Information Science Practice Group Report Boat Map Project Name Development of Boat map to display the position of boats A Group Name Group A /Project No. 14-A
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2013 Future University-Hakodate 2013 System Information Science Practice Group Report Project Name Exploring recipe for a new concept of food B Group Name Group B /Project No. 1-B /Project Leader 1011013
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