Volume 8, Issue 6, June 2016

 

 

 

A Method to Improve the Accuracy of K-Nearest Neighbor Algorithm

Pages: 90-95 (6) | [Full Text] PDF (300 KB)
M Kuhkan
Department Of Computer Engineering, Malayer Branch, Islamic Azad University, Malayer, Iran

Abstract - K-Nearest Neighbor Algorithm (Knn) is one of the best and most widely used classification algorithms with a variety of applications. One of the most important challenges to the application of the algorithm is the same impact of all characteristics in doing the classification, while some of the characteristics are less important for classification; this may deviate the process of classification and reduce the accuracy of the Knn algorithm.Using a new method in this study, a certain weight is allocated to various features based on their importance, so that the same effect of all features is avoided in doing the classification and deviation of classification process, thereby increasing the accuracy of Knn algorithm classification. The comparison of the results of the proposed algorithm implementation and five other classification algorithms on 10 datasets selected from UCI repository indicated the considerable improvement of the classification by the algorithm.
 
Index Terms - Knn Algorithm, Accuracy Improvement, Data Mining, Classification

Citation - M Kuhkan. "A Method to Improve the Accuracy of K-Nearest Neighbor Algorithm ." International Journal of Computer Engineering and Information Technology 8, no. 6 (2016): 90-95.
 

Remote Control Rescue Robotic Boat for Search Operation

Pages: 96-99 (4) | [Full Text] PDF (244 KB)
M Iqbal
Electrical Engineering Department, Sarhad University of Science & IT, Peshawar, Pakistan

Abstract - The aim of this project is that we will design such a robotic boat which will help us to find those cars plans and other metal things which drowned in the river or in the sea or in the pound. We can control the robotic boat while sitting outside the sea or river. We can make it to move right, left, forward by controlling it through remote using visual basic the signal will be send through transmitter and received by receiver. The direction of the boat will be changed through propellers with which motors are connected. In this boat we will install under water wireless camera, which will indicate us about the thing which are drowned under the water and it will tell us by switching on and off the desired light which will be used as an alarm, that where are our drowned things under the water. It will also help us in rescue work.
 
Index Terms - Rescue Boot, Search Operation, Remote Control

Citation - M Iqbal. "Remote Control Rescue Robotic Boat for Search Operation ." International Journal of Computer Engineering and Information Technology 8, no. 6 (2016): 96-99.
 

A Comparison of FAST, SURF, Eigen, Harris, and MSER Features
Pages: 100-105 (6) | [Full Text] PDF (910 KB)
E Ali, EU Khan, EZ Mahmudi, R Ullah
Sarhad University Peshawar

Abstract - Precise, successful in desire target, strong healthy and self loading image registration is critical task in the field of computer vision. The most require key steps of image alignment/registration are: Feature matching, Feature detection, , derivation of transformation function based on corresponding features in images and reconstruction of images based on derived transformation function. This is also the aim of computer vision in many applications to achieve an optimal and accurate image, which depends on optimal features matching and detection. The investigation of this paper summarize the coincidence among five different methods for robust features/interest points (or landmarks) detector and indentify images which are (FAST), Speed Up Robust Features (SURF), (Eigen),( Harris) & Maximally Stable Extremal Regions ( MSER). This paper also focuses on the unique extraction from the images which can be used to perform good matching on different views of the images/objects/scenes.
 
Index Terms - Feature detection, Feature matching, FAST, SURF, EIGEN, HARIS and MSER

Citation - E Ali, EU Khan, EZ Mahmudi, R Ullah. "A Comparison of FAST, SURF, Eigen, Harris, and MSER Features." International Journal of Computer Engineering and Information Technology 8, no. 6 (2016): 100-105.