Search Results - subject:"Machine Learning"

Fast HEVC Inter-Prediction Algorithm Based on Matching Block Features

Liu, Meifeng; Zhong, Guoyun; He, Yueshun; Zhong, Kai; … - In: International Journal of Mobile Computing and … 9 (2018) 1, pp. 40-61

A fast inter-prediction algorithm based on matching block features is proposed in this article. The position of the matching block of the current CU in the previous frame is found by the motion vector estimated by the corresponding located CU in the previous frame. Then, a weighted motion vector...

Persistent link: https://www.econbiz.de/10012046485

Machine Learning Classification of Tree Cover Type and Application to Forest Management

MacMichael, Duncan; Si, Dong - In: International Journal of Multimedia Data Engineering … 9 (2018) 1, pp. 1-21

This article is driven by three goals. The first is to use machine learning to predict tree cover types, helping to … machine learning models: Naïve Bayes, Decision Tree, and K-Nearest Neighbor (KNN). The neural network model achieved 91 … model performed 20.97% better than the past neural networks, which illustrates both advances in machine learning algorithms …

Persistent link: https://www.econbiz.de/10012046533

Improving Auto-Detection of Phishing Websites using Fresh-Phish Framework

Shirazi, Hossein; Haefner, Kyle; Ray, Indrakshi - In: International Journal of Multimedia Data Engineering … 9 (2018) 1, pp. 51-64

-Phish”, for creating current machine-learning data for phishing websites. The improved framework uses a total of 28 different … website features that query using python, then a large labeled dataset is built and analyze over several machine learning …

Persistent link: https://www.econbiz.de/10012046536

Learning Avatar's Locomotion Patterns Through Spatial Analysis in FPS Video Games

Santillan, Luis Alberto Casillas; Gonzalez, Johor … - In: International Journal of Organizational and Collective … 8 (2018) 1, pp. 28-45

these patterns would allow an improved game response and even the possibility of machine learning, as well as other …

Persistent link: https://www.econbiz.de/10012046779

Severity Assessment of a Reported Bug by Considering its Uncertainty and Irregular State

Kumari, Madhu; Sharma, Meera; Singh, V. B. - In: International Journal of Open Source Software and … 9 (2018) 4, pp. 20-46

authors have predicted the bug severity by using machine learning techniques, namely KNN, J48, RF, RNG, NB, CNN and MLR. They …

Persistent link: https://www.econbiz.de/10012047000

Machine Learning in Healthcare, Introduction and Real World Application Considerations

Pitoglou, Stavros - In: International Journal of Reliable and Quality … 7 (2018) 2, pp. 27-36

Machine Learning, closely related to Artificial Intelligence and standing at the intersection of Computer Science and … understand the inherent causalities/patterns and apply conventional methods towards an acceptable solution, Machine Learning can … find a fertile field of application. This article's purpose is to give a general non-technical definition of Machine …

Persistent link: https://www.econbiz.de/10012047333

Using Non-Intrusive Environmental Sensing for ADLS Recognition in One-Person Household

Saiki, Sachio; Niu, Long; Nakamura, Masahide - In: International Journal of Software Innovation (IJSI) 6 (2018) 4, pp. 16-29

kinds of environment attributes. The system then applies machine-learning techniques to predict 7 kinds of ADLS. Finally …

Persistent link: https://www.econbiz.de/10012047822

Research on Facial Expression Recognition Technology Based on Convolutional-Neural-Network Structure

Guo, Junqi; Shan, Ke; Wu, Hao; Bie, Rongfang; You, Wenwan; … - In: International Journal of Software Innovation (IJSI) 6 (2018) 4, pp. 103-116

Human facial expressions change so subtly that recognition accuracy of most traditional approaches largely depend on feature extraction. In this article, the authors employ a deep convolutional neural network (CNN) to devise a facial expression recognition system to discover deeper feature...

Persistent link: https://www.econbiz.de/10012047828

An Analysis of Motion Transition in Subtle Errors using Inductive Logic Programming: A Case Study in Approaches to Mild Cognitive Impairment

Ohwada, Hayato; Martono, Niken Prasasti; Abe, Keisuke; … - In: International Journal of Software Science and … 10 (2018) 1, pp. 27-37

This article seeks to utilize the data collected from virtual reality (VR)-based software and a leap-motion device used for learning of subtle errors in mild cognitive impairment (MCI) cases to enable early detection of MCI by analyzing the classification rules for errors (action slips) based on...

Persistent link: https://www.econbiz.de/10012048055

Predicting Reasoner Performance on ABox Intensive OWL 2 EL Ontologies

Li, Yuan-Fang; Pan, Jeff Z.; Bobed, Carlos; Guclu, Isa; … - In: International Journal on Semantic Web and Information … 14 (2018) 1, pp. 1-30

In this article, the authors introduce the notion of ABox intensity in the context of predicting reasoner performance to improve the representativeness of ontology metrics, and they develop new metrics that focus on ABox features of OWL 2 EL ontologies. Their experiments show that taking into...

Persistent link: https://www.econbiz.de/10012048279