Deep Learning Techniques to Classify the Aerial Images with Gabor Filter

Deep Learning Techniques to Classify the Aerial Images with Gabor Filter

Prakruthi D P

PG Scholar Computer science and Engineering

Er. Perumal Manimekalai College of Engineering Hosur,India

P Sumathi

Assistant Professor Computer science and            Engineering

Er.Perumal Manimekalai College of  Engineering ,Hosur,India

Abstract - Aerial Images are a valuable data source for earth observation, can help us to measure and observe detailed structures on the Earth’s surface. Aerial images are drastically growing. This has given particular urgency to the quest for how to make full use of ever-increasing Aerial images for intelligent earth observation. Hence, it is extremely important to understand huge and complex Aerial images.

Aerial image classification, which aims at labeling Aerial images with a set of semantic categories based on their contents, has broad applications in a range of fields. Propelled by the powerful feature learning capabilities of deep neural networks, Aerial image scene classification driven by deep learning has drawn remarkable attention and achieved significant breakthroughs.

However, recent achievements regarding deep learning for scene classification of Aerial images is still lacking.

Keywords – Deep learning, Aerial image, CNN, Gabor Filter.