Programs
- M. Tech. in Automotive Engineering -
- Fellowship In Interventional Pulmonology and Pulmonary Critical care - Fellowship
Publication Type : Conference Paper
Publisher : 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE)
Source : 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE), 2019
Url : https://ieeexplore.ieee.org/document/8979114
Keywords : Jupyter notebook, anaconda prompt, Machine learning, artificial intelligence, deep convolutional neural networks, computer vision, image classification, k clusters algorithm, HSV values
Campus : Amritapuri
Center : Humanitarian Technology (HuT) Labs
Year : 2019
Abstract : This paper presents the novel idea for detecting food spoilage using image classification with machine learning algorithms and artificial intelligence technology. Food spoilage is detected by using artificial intelligence, deep convolutional neural networks, and computer vision and machine learning algorithms like k clusters algorithm for color classifications in images and its HSV values for spoilage detection. This project is done using the jupyter notebook platform through anaconda prompt. In this project, photos of food or fruits will be taken which have to be tested and then it will be processed through computer which will then perform image classification and machine learning algorithms for getting the colors in the image and spoilage is detected by HSV (Hue Saturation Value) values and percentages of each color which we have got by using the k cluster algorithms in jupyter notebook.
Cite this Research Publication : Rajesh Kannan Megalingam;GaddeSakhitaSree;Gunnam Monika Reddy;Inti Rohith Sri Krishna;L.U. Suriya, "Food Spoilage Detection Using Convolutional Neural Networks and K Means Clustering", 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE), 2019