28 research outputs found
CNN Based Posture-Free Hand Detection
Although many studies suggest high performance hand detection methods, those
methods are likely to be overfitting. Fortunately, the Convolution Neural
Network (CNN) based approach provides a better way that is less sensitive to
translation and hand poses. However the CNN approach is complex and can
increase computational time, which at the end reduce its effectiveness on a
system where the speed is essential.In this study we propose a shallow CNN
network which is fast, and insensitive to translation and hand poses. It is
tested on two different domains of hand datasets, and performs in relatively
comparable performance and faster than the other state-of-the-art hand
CNN-based hand detection method. Our evaluation shows that the proposed shallow
CNN network performs at 93.9% accuracy and reaches much faster speed than its
competitors.Comment: 4 pages, 5 figures, in The 10th International Conference on
Information Technology and Electrical Engineering 2018, ISBN:
978-1-5386-4739-
Towards Indonesian Speech-Emotion Automatic Recognition (I-SpEAR)
Even though speech-emotion recognition (SER) has been receiving much
attention as research topic, there are still some disputes about which vocal
features can identify certain emotion. Emotion expression is also known to be
differed according to the cultural backgrounds that make it important to study
SER specific to the culture where the language belongs to. Furthermore, only a
few studies addresses the SER in Indonesian which what this study attempts to
explore. In this study, we extract simple features from 3420 voice data
gathered from 38 participants. The features are compared by means of linear
mixed effect model which shows that people who are in emotional and
non-emotional state can be differentiated by their speech duration. Using SVM
and speech duration as input feature, we achieve 76.84% average accuracy in
classifying emotional and non-emotional speech.Comment: 4 pages, 3 tables, published in 4th International Conference on New
Media (Conmedia) on 8-10 Nov. 2017 (http://conmedia.umn.ac.id/) [in print as
in Sept. 17, 2017
Do you see what I see? Taking perspective of others using facial images
Albeit many HCI / emotion recognition studies use facial expressive images,
few scrutinize the accuracies of the people (experimenters and participants) in
perceiving the expressions representing the intended emotions. The
misinterpretation of the expression will put bias in the data and introduce
questions on the validity of the studies. The possibility of misinterpretation
of the expressions will be the focus of the experiment conducted in this study.
The experiment will evaluate the ability of people in taking the perspective of
others in spite of their current emotions and gender, and whether the
expressions can be universally perceived. This study find that it is relatively
safe to use facial expressive images for research as long as the emotions are
exclusively within the six basic emotions.Comment: 6 pages, 3 figures, In 2018 4th International Conference on Science
and Technology (ICST
Simple Text Mining for Sentiment Analysis of Political Figure Using Naive Bayes Classifier Method
Text mining can be applied to many fields. One of the application is using
text mining in digital newspaper to do politic sentiment analysis. In this
paper sentiment analysis is applied to get information from digital news
articles about its positive or negative sentiment regarding particular
politician. This paper suggests a simple model to analyze digital newspaper
sentiment polarity using naive Bayes classifier method. The model uses a set of
initial data to begin with which will be updated when new information appears.
The model showed promising result when tested and can be implemented to some
other sentiment analysis problems.Comment: 5 pages, published in the Proceedings of the 7th ICT
Circle-based Eye Center Localization (CECL)
We propose an improved eye center localization method based on the Hough
transform, called Circle-based Eye Center Localization (CECL) that is simple,
robust, and achieves accuracy on a par with typically more complex
state-of-the-art methods. The CECL method relies on color and shape cues that
distinguish the iris from other facial structures. The accuracy of the CECL
method is demonstrated through a comparison with 15 state-of-the-art eye center
localization methods against five error thresholds, as reported in the
literature. The CECL method achieved an accuracy of 80.8% to 99.4% and ranked
first for 2 of the 5 thresholds. It is concluded that the CECL method offers an
attractive alternative to existing methods for automatic eye center
localization.Comment: Published and presented at The 14th IAPR International Conference on
Machine Vision Applications, 2015. http://www.mva-org.jp/mva2015
Warehouse Layout Method Based on Ant Colony and Backtracking Algorithm
Warehouse is one of the important aspects of a company. Therefore, it is
necessary to improve Warehouse Management System (WMS) to have a simple
function that can determine the layout of the storage goods. In this paper we
propose an improved warehouse layout method based on ant colony algorithm and
backtracking algorithm. The method works on two steps. First, it generates a
solutions parameter tree from backtracking algorithm. Then second, it deducts
the solutions parameter by using a combination of ant colony algorithm and
backtracking algorithm. This method was tested by measuring the time needed to
build the tree and to fill up the space using two scenarios. The method needs
0.294 to 33.15 seconds to construct the tree and 3.23 seconds (best case) to
61.41 minutes (worst case) to fill up the warehouse. This method is proved to
be an attractive alternative solution for warehouse layout system.Comment: 5 pages, published in proceeding of the 14th IAPR International
Conference on Quality in Research (QIR
Do you see what I see? Taking perspective of others using facial images
Albeit many HCI / emotion recognition studies use facial expressive images, few scrutinize the accuracies of the people (experimenters and participants) in perceiving the expressions representing the intended emotions. The misinterpretation of the expression will put bias in the data and introduce questions on the validity of the studies. The possibility of misinterpretation of the expressions will be the focus of the experiment conducted in this study. The experiment will evaluate the ability of people in taking the perspective of others in spite of their current emotions and gender, and whether the expressions can be universally perceived. This study find that it is relatively safe to use facial expressive images for research as long as the emotions are exclusively within the six basic emotions
Application distribution model in volunteer computing environment using peer-to-peer torrent like approach
Volunteer computing has been known as an alternative solution to solve complex problems. It is acknowledged for its simplicity and its ability to work on multiple operating systems. Nonetheless, setting up a server for volunteer computing can be time consuming and relatively complex to be implemented. This paper offer a model which can ease the effort of setting up a server by making the agent works two ways, as seeder and leecher, like P2P torrent approaches. The model consists of measurement units to manage applications to be distributed, system hierarchy, and basic procedures for the server and the agent. The model has been tested in four scenarios using 2,000,000 to 3,000,000 integer data employing up to six nodes. The tests demonstrate speedup in three of the scenarios