Object Recognition in Image Sequence using Heuristic Convolution Neural Network
Mahesh Kini M
Mahesh Kini M, Department of Computer Science and Engineering, N.M.A.M. Institute of Technology, Nitte, Udupi, India.
Manuscript received on September 19, 2019. | Revised Manuscript received on October 05, 2019. | Manuscript published on October 30, 2019. | PP: 520-525 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9644109119/2019©BEIESP | DOI: 10.35940/ijeat.A9644.109119
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The human visual system can make a distinction of tiger from cat very easily without taking any efforts. But in case of a computer system, it is a very complicated job. Identifying and differentiating task has to deal with many challenges but the human brain makes it effortless. Self learning or heuristic techniques are most relevant in this area. The recognition task is to search for the particular object of same shape, color and texture and so on, of the trained objects and match with input. The geometrical distinction such as zoom in, zoom out, rotation etc result in poor performance. This paper uses convolution neural network models Alexnet and VGG Net on object recognition problems which are added with novel heuristic method. We have used CIFAR-10 dataset. The performance and computation speeds are found efficient.
Keywords: Component; Convolution neural networks; object recognition; Feature extraction; Classification; Alex Net; VGG Net;