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About Animal Detection 1
This document is a project report submitted in partial fulfillment of a Bachelor's degree in Electronic and Communication Engineering. The project focuses on identifying and classifying wildlife species from camera trap images using computer vision and machine learning techniques. Specifically, the project aims to classify animal species in the Missouri Camera Traps dataset using deep convolutional neural network architectures like InceptionV3, MobileNet, and VGG-16. The results show that InceptionV3 achieves an accuracy of 69.5% for six animal classes in the dataset. Transfer learning is also used to pre-train models to identify rare classes in other datasets.
Detailed Information
| Author: | ['Mohamed aslam'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 56 |
| Language: | English |
| Format: | |
| Price: | FREE |
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