A Novel Model for Visual Content Based Image Retrieval using Transfer Learning
Amit Sharma1, V. K. Singh2, Pushpendra Singh3
1Amit Sharma, Assistant Professor, Department of Computer Science and Engineering, Motherhood University, Roorkee (Uttarakhand), India.
2Dr. V. K. Singh, Department of Mathematics, Indian Institute of Technology Varanasi, (U.P), India.
3Dr. Pushpendra Singh, Associate Professor, Department of Information Technology, Raj Kumar Goel Institute of Technology, Ghaziabad (U.P), India.
Manuscript received on 17 July 2022 | Revised Manuscript received on 27 July 2022 | Manuscript Accepted on 15 August 2022 | Manuscript published on 30 August 2022 | PP: 101-107 | Volume-11 Issue-6, August 2022 | Retrieval Number: 100.1/ijeat.F37250811622 | DOI: 10.35940/ijeat.F3725.0811622
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© 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: At present, the revolution brought by deep learning based technologies in the field of computer vision gaining momentum in the world of artificial intelligence. In particular, the best models for retrieving common images today are based on features generated by deep convolutional neural networks (DCNNs). However, this great success was expensive. A comprehensive amount of tagged data had to be collected, followed by model design and training. Meanwhile, a transfer-oflearning approach has been developed that avoids this costly step by applying a sophisticated, pre-trained generic DCNN model to completely different data domains. With the use of transfer learning, it becomes possible to use deep CNN models for small datasets with better retrieval performance with respect to handcrafted feature based retrieval methods. In this paper a deep CNN based model has been proposed which uses concept of transfer learning and achieves good classification accuracy.
Keywords: Deep Convolutional Neural Network, Transfer Learning, Pre-trained Networks, Visual content based Image Search and Retrieval
Scope of the Article: Deep Convolutional Neural Network