CRUD IMAGE PARADIGM USING DEEP LEARNING ALGORITHM

CRUD IMAGE PARADIGM USING DEEP LEARNING ALGORITHM

ARVAPALLI SIRISHA1,KOMMINI LAKSHMI PRIYA2, VALLURU ANJANA PRIYA3

1Arvapalli Sirisha, Department of Information Technology & Dhanekula Institute of Engineering and Technology

2Kommini Lakshmi Priya, Department of  Electronics & Communication Engineering & Dhanekula Institute of Engineering and Technology

3Valluru Anjana Priya, Department of  Electronics & Communication Engineering & Dhanekula Institute of Engineering and Technology

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Abstract - Pollution is becoming a serious issue all around the world. That contamination can arise as a result of waste items that cannot be decomposed, such as plastic, certain metals, medical waste, and so on, resulting in severe soil pollution. Soil contamination can have serious consequences for the environment by diminishing soil organic matter and the soil's ability to operate as a filter. However, this is the ideal answer for this situation because it classifies waste as bio or non-bio. A neural network based on the textural properties of the images allows for the classification of normal images while distinguishing them from cancerous ones. To address this issue, CNN algorithms for image detection have been proposed. The algorithm has a detection precision of 90%. The results suggest that autonomous waste classification using image processing and artificial intelligence is possible.

Key Words:  Soil pollution, CNN algorithms, classification, image processing, artificial intelligence