BORDER DEFENCE MECHANISM CLASSIFICATION USING DEEP LEARNING TECHNIQUES

Abstract

ABSTRACT --The creation of strong defence crucial when it comes to border security and national security. Conventional border defense tactics frequently rely on manual surveillance and human intervention, which can be resource-intensive and prone to human mistake. This work suggests a novel method for classifying border defence mechanisms that makes use of deep learning techniques. Designing and implementing an intelligent system that can automatically classify and detect different border defence measures, like walls, fences, trenches, and sensor-based systems, using photographs and sensor data is the main goal of this project. Model parameters will be adjusted during the training phase using optimisation approaches to guarantee peak performance.