检索结果-内蒙古大学图书馆

Comparison Between Neural Network and Support Vector Machine in Optical Character Recognition

Procedia computer science 2017年 116卷 351-357页

作者： Michael Reynaldo Phangtriastu Jeklin Harefa Dian Felita Tanoto Computer Science Department School of Computer Science Bina Nusantara University Jl. KH Syahdan 9 Jakarta 11480 Indonesia

Optical Character Recognition is one of the popular area in artificial intelligence and pattern recognition area. Generally, this technique converts the input image into an editable format in computer. This paper uses several techniques as a comparison for some extracted features, such as: zoning algorithm, projection profile, Histogram of Oriented Gradients (HOG) and combination of those feature extractions ( zoning + projection, projection + HOG, zoning + HOG, zoning + projection + HOG). For the evaluation of the proposed system, this paper compare the most commonly classifiers: Support Vector Machine (SVM) and Artificial Neural Network (ANN). This experiment achieves the highest accuracy of 94.43% using Support Vector Machine (SVM) classifier with the feature extraction algorithms are:projection profile and the combination of zoning + projection profile

关键词： Optical Character Recognition Support Vector Machine Artificial Neural Network

来源：评论

学校读者我要写书评

暂无评论

Mango Fruit Sortation System using Neural Network and computer Vision

引用

Procedia computer science 2017年 116卷 596-603页

作者： Emny Harna Yossy Jhonny Pranata Tommy Wijaya Heri Hermawan Widodo Budiharto Computer Science Department School of Computer Sciences Bina Nusantara University Syahdan Campus Jakarta 11480 Indonesia

Mango has different colors and sizes that indicate the level of maturity. Mango maturity level often makes farmers confused when choosing a mango that has a good maturity. Sometimes, mango farmers still use manual methods to distinguish mango maturity, while the way that human labor is often inaccurate and different in its determination. The difference is due to the different perceptions of each person. From these problems then the need of machine sorting system on agriculture is felt important. Therefore, researchers will conduct research on mango sortation system. Mango has many types such as “Harum Manis”, “Apple”, “Gincu”, etc. In this study type of mango that will be studied is mango “Gincu” because has a good color distribution. The goal of the research is to create a system that can sort mango that ripe or unripe. The method that used to do this research is separated into few step: problem identification, algorithm development, implementation and evaluation. The system is made using C language, computer Vision and ANN (Artificial Neural Network) so the system can detect the color of mango that has been ripe or unripe. The output of this research will be compared to related research. The final output of this research is the system can detect the ripe or unripe mango with 94% accuracy.

关键词： computer Vision Artifial Intelligence Neural Network Black Propagation

来源：评论

学校读者我要写书评

暂无评论

Crowdsourcing annotation system of object counting dataset for deep learning algorithm

引用

IOP Conference Series: Earth and Environmental science 2018年第1期195卷

作者： Tjeng Wawan Cenggoro Fidelson Tanzil Ayu Hidayah Aslamiah Ettikan Kandasamy Karuppiah Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 NVIDIA Corporation Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Deep Learning is currently the state-of-the-art technique for various computer Vision tasks, including object counting. Despite of its high performance, Deep Learning requires a gigantic amount of training data to show its best result. Getting this massive data in reasonable time requires a proper strategy such as crowdsourcing. However, in case of object counting, we found no crowdsourcing system able to effectively collect necessary data. To tackle this problem, we develop a crowdsourcing system to annotate image for object counting dataset. This system is also equipped with validation system to ensure the quality of collected dataset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Learning Culture Framework in E-Learning for the Equivalency Education program (E-LEEP Culture)

引用

Journal of Physics: Conference Series 2019年第1期1235卷

作者： Mesra Betty Yel Sfenrianto Sfenrianto Gunawan Wang Faculty of Computer Science STIKOM CKI Jakarta Indonesia Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480

Understanding learning culture based on learning activities is important for learning success in an e-Learning. As an effort that can be done for this purpose, it is necessary to build a student learning culture based on students activities. The study proposes a Cultural Framework for Learning in an E-Learning. It is called E-LEEP Culture because used in an e-Learning the Equality Education program (E-LEEP). This framework has five key components, namely: Students, E-LEEP, Learning Activities, Learning Culture, and Digital Contents. Learning culture component in E-LEEP Culture Framework consists of sharing activities, getting information, discussingIndividualistic Learning, Collaborative Learning, Learning Time (learn a little), and Learning Time (learn a lot). Each of the components is expected as a basis for providing learning material that suits the needs of students.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Strategy using Social Media to Increase Students Engagement in E-Learning for the Equivalency Education program (E-LEEP)

引用

Journal of Physics: Conference Series 2019年第1期1235卷

作者： Mesra Betty Yel Sfenrianto Sfenrianto Gunawan Wang Ahmad Nurul Fajar Faculty of Computer Science STIKOM CKI Jakarta Indonesia Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480

Social media can be used to support learning activities in non-formal education. The utilization of social media by students can be seen as a strategy to improve the students' engagement in e-Learning. It is an important goal for the e-Learning of non-formal education. This study aims to propose a strategy using social media to increase students engagement in E-Learning for the Equivalency Education program (SosMed E-LEEP strategy). This strategy has several key components. These components are students, social media, E-LEEP, and Students Engagement. SosMed E-LEEP Strategy consists of sharing activities, getting information, discussing, and interacting with students and Tutor, and for learning purpose. Each of these strategic activities is expected to improve students engagement, namely: access to learning materials, forum discussion activities, and assignment uploading.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Preface

引用

Procedia computer science 2018年 135卷 1-1页

作者： Budiharto, Widodo Gunawan, Alexander A.S. Wulandhari, Lili Ayu Williem Faisal Sutoyo, Rhio Meiliana Suryani, Dewi Arifin, Yulyani Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

来源：评论

学校读者我要写书评

暂无评论

Harmonik = ++(Web IDE)

引用

Procedia computer science 2017年 116卷 222-231页

作者： Budi Yulianto Harjanto Prabowo Raymond Kosala Manik Hapsara Management Department BINUS Business School Undergraduate Program Bina Nusantara University Indonesia Computer Science Department Faculty of Computing and Media Bina Nusantara University Indonesia

IDE (Integrated Development Environment) that is needed by developers to write sourcecode for computer programming is also starting to shift from desktop to web platform. As implemented in the cloud, Web IDE (WIDE) can be accessed online through browsers and on mobile devices. WIDE takes many advantages and becomes popular in recently years. Unfortunately, there is no tool found yet in currently WIDE to support translating novice programmers’ algorithm into programming language before they become experts in techniques of writing computer programs. This study goal is to design a tool to support novice programmers’ early learning of programming before they step into coding, compiling, running, and debugging in WIDE. Software development method used in this study is Rational Unified Process (RUP). Conclusion of this study is block-code tool can help novice programmers to learn programming language in early phase, and motivate them better.

关键词： Web IDE Online IDE Cloud IDE Mobile IDE Browser IDE Integrated Development Environment

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Hand Detection in Class Room Using Combination of Skin Detection and Hough Transform

引用

Procedia computer science 2017年 116卷 516-522页

作者： Hanry Ham Felix Jingga Dewi Suryani Irene Anindaputri Siswanto Computer Science Department School of Computer Science Bina Nusantara University Jl. KH. Syahdan No. 9 Jakarta 11480 Indonesia

A large number of dataset can take a lot of effort in order to annotate the object that we observe, in this work is hand object. Therefore, we introduce an image processing method in order to perform unsupervised hand detection. The algorithm does not require any annotation data in order to do hand detection. Image processing step starts from skin detection in order to differentiate skin and non-skin region respectively. Subsequently, the border elimination was performed by specifying coordinates of each categories in dataset. Hand detection was performed by applying canny edge detector combined with hough transform in order to the hand coordinate. The proposed pipeline is validated by three categories of dataset. The result allows good accuracy rates of up to 97,677%.

关键词： Interactive Presentation Skin Detection Unsupervised Hand Detection Class Room Multimedia Tool

来源：评论

学校读者我要写书评

暂无评论

Author Correction: Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

引用

Nature genetics 2023年第3期55卷 519-520页

作者： Ceres Fernandez-Rozadilla Maria Timofeeva Zhishan Chen Philip Law Minta Thomas Stephanie Schmit Virginia Díez-Obrero Li Hsu Juan Fernandez-Tajes Claire Palles Kitty Sherwood Sarah Briggs Victoria Svinti Kevin Donnelly Susan Farrington James Blackmur Peter Vaughan-Shaw Xiao-Ou Shu Jirong Long Qiuyin Cai Xingyi Guo Yingchang Lu Peter Broderick James Studd Jeroen Huyghe Tabitha Harrison David Conti Christopher Dampier Mathew Devall Fredrick Schumacher Marilena Melas Gad Rennert Mireia Obón-Santacana Vicente Martín-Sánchez Ferran Moratalla-Navarro Jae Hwan Oh Jeongseon Kim Sun Ha Jee Keum Ji Jung Sun-Seog Kweon Min-Ho Shin Aesun Shin Yoon-Ok Ahn Dong-Hyun Kim Isao Oze Wanqing Wen Keitaro Matsuo Koichi Matsuda Chizu Tanikawa Zefang Ren Yu-Tang Gao Wei-Hua Jia John Hopper Mark Jenkins Aung Ko Win Rish Pai Jane Figueiredo Robert Haile Steven Gallinger Michael Woods Polly Newcomb David Duggan Jeremy Cheadle Richard Kaplan Timothy Maughan Rachel Kerr David Kerr Iva Kirac Jan Böhm Lukka-Pekka Mecklin Pekka Jousilahti Paul Knekt Lauri Aaltonen Harri Rissanen Eero Pukkala Johan Eriksson Tatiana Cajuso Ulrika Hänninen Johanna Kondelin Kimmo Palin Tomas Tanskanen Laura Renkonen-Sinisalo Brent Zanke Satu Männistö Demetrius Albanes Stephanie Weinstein Edward Ruiz-Narvaez Julie Palmer Daniel Buchanan Elizabeth Platz Kala Visvanathan Cornelia Ulrich Erin Siegel Stefanie Brezina Andrea Gsur Peter Campbell Jenny Chang-Claude Michael Hoffmeister Hermann Brenner Martha Slattery John Potter Konstantinos Tsilidis Matthias Schulze Marc Gunter Neil Murphy Antoni Castells Sergi Castellví-Bel Leticia Moreira Volker Arndt Anna Shcherbina Mariana Stern Bens Pardamean Timothy Bishop Graham Giles Melissa Southey Gregory Idos Kevin McDonnell Zomoroda Abu-Ful Joel Greenson Katerina Shulman Flavio Lejbkowicz Kenneth Offit Yu-Ru Su Robert Steinfelder Temitope Keku Bethany van Guelpen Thomas Hudson Heather Hampel Rachel Pearlman Sonja Berndt Richard Hayes Marie Elena Martinez Sushma Thomas Douglas Corley Paul Pharoah Susanna Larsson Yun Yen Heinz-Jo Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK. Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain. Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark. Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA. Division of Genetics and Epidemiology Institute of Cancer Research London UK. Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA. Genomic Medicine Institute Cleveland Clinic Cleveland OH USA. Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA. Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain. Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain. Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain. Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain. Department of Biostatistics School of Public Health University of Washington Seattle WA USA. Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK. Department of Public Health Richard Doll Building University of Oxford Oxford UK. Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA. Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA. Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA. De

来源：评论

学校读者我要写书评

暂无评论

Location-based game to enhance player’s experience in survival horror game

引用

Procedia computer science 2017年 116卷 206-213页

作者： Yen Lina Prasetio Rendy Wijaya Michael Pratama Sjah Michael Ryan Christian Andry Chowanda Computer Science Department School of Computer Science Bina Nusantara University Jl. KH. Syahdan No. 9 Jakarta 11480 Indonesia

This paper aims to explore the possibility of implementing location-based game using the smartphone’s GPS to enhance the player’s experience. With the GPS technology, the player can play in a real world as well as in the virtual game world. We postulate this thus will enhance the player’s experience. To test the hypothesis, a horror game genre with location-based features was developed. The game was evaluated to thirty participants. The results demonstrate the game allowed the participants to explore a new place with fun. In addition, the participants claimed that the game allow them to enjoy a new experience in playing horror game. The participants described that playing the game was giving them more tension compare to playing a conventional horror game. Moreover, the participants claimed that they feel more familiar with the place they’ve explored during the game. Finally, some improvements could be done to improve the experience enhancement to the game. First, more variation in the storyline, quests and the enemy. As the game evaluated in this paper is served only as a prototype, the variation of the storyline, quests and the enemy (i.e. the ghost) is limited.

关键词： Location-Based Experience Survival Game Horror Game

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：