Object Detection and Semantic Segmentation using Neural Networks

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-47 Number-2
Year of Publication : 2017
Authors : R.Karthika, S. N Santhalakshmi
DOI :  10.14445/22312803/IJCTT-V47P113


R.Karthika, S. N Santhalakshmi "Object Detection and Semantic Segmentation using Neural Networks". International Journal of Computer Trends and Technology (IJCTT) V47(2):95-100, May 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Semantic segmentation and object detection are two most common tasks in the field of digital image processing, classification and segmentation. The object detection in repetition domain will be approached to segment objects from foreground with absence of background noise. This work has introduced one automatically detecting an object to increase the accuracy and yield and decrease the diagnosis time. This proposed method represents image Segmentation and Object Detection using NN classifier. The first step for input image segmentation and feature extracted from segmented image using NN classifier. The goal of Classification is to find Object from input ones. At the end it is shown the object detected image. The best results can be achieved by this proposed image segmentation and classification image.

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Thresholding, GLSM , Probabilistic Neural Networks, Threshold, eigen, Palmprint, vector clustering, kernel tric, semantic segmentation, Down sampling, neural networks, Perceptron, Discrete wavelet, Modeling, simulation, and prototyping, vectors.