Deep Learning Based Multi-class Wild Pest Detection approch Using Mobilenet Algorithm

YEAR : 2022

Description

This project illustrates an automatic approach for pest detection using Deep learning
The core objective of the research is to enhance feature extraction phase to improve the detection efficiency.
The proposed approach is implemented on images of fluffy caterpillar pests on mustard crop and fava bean collected from farms in kaggle web site .The experimental results affirm the efficiency of the proposed approach.

ADDITIONAL INFORMATION

System Requirements

Operating System : Windows 7,8,10 (64 bit)
Software : Python
Tools : Anaconda (Jupyter notebook and anaconda prompt)

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