Autonomous Fruit Recognition System Based on Deep Convolutional Neural Network
Sahana P. Savant1, P.S. Khanagoudar2

1Sahana P. Savant*, Student, Department of Computer Science and Engineering, KLS Gogte Institute of Technology, New Delhi, India.
2Mr. P. S. Khanagoudar, Assistant Professor, Department of Computer Science, KLS Gogte Institute of Technology, New Delhi, India.
Manuscript received on August 07, 2020. | Revised Manuscript received on August 15, 2020. | Manuscript published on August 30, 2020. | PP: 396-404 | Volume-9 Issue-6, August 2020. | Retrieval Number: D9082049420/2020©BEIESP | DOI: 10.35940/ijeat.D9082.089620
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 (

Abstract: Recently it is found that people are becoming more cautious to their diet throughout the universe. Unhealthy diet can cause many problems like sugar, obesity, gain in weight and many other chronic health related issues. Essential part of our diet is contributed by fruits as they are rich source of vitamins, fiber, energy and nutrients. Today’s era has been adapted to a system of intake of foods which has several adverse effects on human health. The proposed system is Autonomous Fruit Recognition system based on Deep Convolutional Neural Network (DCNN) method. Using this technology recognition and estimation of fruit calories is necessary to spread awareness about food habits among people suffering from obesity due to bad food culture and consumption of food .This proposed web/app based system simplifies the calorie measuring process of fruit. The machine learning based API used in our system recognize the fruit and provide calorie content of that fruit. System uses convolutional Neural Network called MobileNet. This web/app based application is user friendly. 
Keywords: Fruit Recognition/ DCNN/ Machine vision/Calorie measurement/MobileNet