Abstract
Abstract: This paper describes the design and implementation of a deployable, multi-modal system executed using Deep Learning with Computer Vision. The system was majorly created using Transfer Learning Algorithms, GoogleNet, and MATLAB, which were then made portable and deployable using a Raspberry Pi with Pi Cam. The neural networks were trained on a dataset consisting of several images and is highly accurate. This system consists of Fire Detection, Face and Intruder Detection, Object Identification, and Animal Identification, and follow me features which are meant to be deployed on a mobile robot such as an autonomous rover, drone, glider, and aquatic robot
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