SATELLITE IMAGE DETECTION USING CNN

Abstract

This project focuses on the development of a Convolutional Neural Network (CNN) deep. learning model
for the automatic detection and classification of objects within satellite images. The project includes
dataset collection, preprocessing, model architecture design, objects detection, post-processing,
evaluation, and explores applications in disaster management, land use planning, agriculture, and
environmental monitoring. The project demonstrates the significance of CNN deep learning in satellite
image analysis for real- world applications. Satellite imagery is an invaluable resource in applications
ranging from environmental monitoring to urban planning and disaster management. This project focuses
on the development of a Convolutional Neural Network (CNN) deep learning model for the automatic
detection and classification of objects within satellite images. The project commences with the collection
of a comprehensive and standardized dataset of satellite images. Preprocessing techniques, including
resizing and normalization, prepare the data for deep learning