PEST IDENTIFICATION USING IMAGE PROCESSING TECHNIQUES IN DETECTING IMAGE PATTERN THROUGH NEURAL NETWORK
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER AND ELECTRONICS TECHNOLOGY
Author(s): BARTOLOME T. TANGUILIG , BOBBY D. GERARDO , JOHNNY L. MIRANDA
Abstract: In rice production, pest invasion is considered as the most challenging task for crop technicians and farmers. Pest invasion can cause serious losses and affect the income of farmers. It is then important to assess their density for pests forecasting decision making. Existing identification techniques of these species comprise of using different traps to detect their presence. However, these traditional methods are labor-intensive and sometimes experts on this field are not available. Another problem is that multiple site and frequent monitoring of rice pests is time consuming and tedious for a crop technician. This can lead to low accuracy and delays in obtaining accurate count of these species. In this study, an identification system was developed to automatically identify the insect pests in the paddy field. Sticky trap was used to capture the insect which continuously monitored by a wireless camera to record the video. Different image processing techniques was utilized to detect an
- Publication Date: 27-Aug-2014
- DOI: 10.15224/978-1-63248-024-8-10
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ACADEMIC DECISION SUPPORT SYSTEM FOR COLLEGE COMPLETION MODEL
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER AND ELECTRONICS TECHNOLOGY
Author(s): BARTOLOME T. TANGUILIG , BOBBY D. GERARDO , ALLEN M. PAZ
Abstract: Universities need to have extensive capabilities in order to analyze students’ achievement levels which will help in making appropriate academic decisions. Conversely, academic decisions will result in changes in academic performance which need to be assessed periodically and over spans of time. In this work, the college completion model based on k-means clustering algorithm was utilized in the development of the proposed academic decision support system (DSS). The system utilized data from the university database while the client front-end ensures adequate presentation so as to reveal significant details and dependencies. The system can be used to automate the decision making process of administrators aiming to decrease the high rate of academic failure among students. A real case study in Isabela State University is presented using a dataset collected from 2009-2013.
- Publication Date: 27-Aug-2014
- DOI: 10.15224/978-1-63248-024-8-11
- Views: 0
- Downloads: 0