Implementation of Tensor Flow for Real-time Object Detection
R. Aroul Canessane1, R. Dhanalakshmi2, V. Maria Anu3
1R. Aroul Canessane, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
2R. Dhanalakshmi, Jeppiaar Engineering College, Chennai (Tamil Nadu), India.
3V. Maria Anu, Sathyabama Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 15 October 2019 | Revised Manuscript received on 24 October 2019 | Manuscript Published on 02 November 2019 | PP: 2342-2345 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B12650982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1265.0982S1119
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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: Tensor Flow is an open-source Machine Learning library for research and creation. Tensor Flow offers APIs for beginners and specialists to create for work desktop, mobile, web, and cloud. The best utilizations of Google’s Tensor flow are the best applications for deep learning . Deep Learning is extraordinary at example acknowledgment/machine recognition, and it’s being connected to pictures, video, sound, voice, content and time arrangement information. It groups and bunch information like that with now and again superhuman precision. This can be actualized for the acknowledgment of the diverse items, for example, Ball, Cat, Bottle, Car and so forth. It can utilize Android as its stage with to utilize the cell phone’s camera to prepare the informational indexes and perceive diverse items in ongoing process.
Keywords: Deep learning, Tensor Flow, CNN, Face Acknowledgment, Support Vector Machine.
Scope of the Article: Real-Time Information Systems