PROJECT TITLE :

Convolutional Neural Network Based Automatic Object Detection on Aerial Images

ABSTRACT:

We are witnessing daily acquisition of enormous amounts of aerial and satellite imagery. Analysis of such giant quantities of data can be useful for several practical applications. In this letter, we tend to present an automatic content-based analysis of aerial imagery so as to detect and mark arbitrary objects or regions in high-resolution pictures. For that purpose, we tend to proposed a method for automatic object detection based on a convolutional neural network. A novel 2-stage approach for network training is implemented and verified within the tasks of aerial image classification and object detection. Initial, we tested the proposed coaching approach using UCMerced data set of aerial images and achieved accuracy of approximately ninety eight.half-dozen%. Second, the strategy for automatic object detection was implemented and verified. For implementation on GPGPU, a required processing time for one aerial image of size 5000 5000 pixels was around thirty s.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : The Devil Is in the Details An Efficient Convolutional Neural Network for Transport Mode Detection ABSTRACT: The objective of the classification problem known as transport mode detection is to devise an algorithm
PROJECT TITLE : Real-Time Tracking Algorithm for Aerial Vehicles Using Improved Convolutional Neural Network and Transfer Learning ABSTRACT: A real-time tracking algorithm that makes use of an improved convolutional neural network
PROJECT TITLE : On Smart Gaze based Annotation of Histopathology Images for Training of Deep Convolutional Neural Networks ABSTRACT: To fully realize the potential of deep learning in histopathology applications, a bottleneck
PROJECT TITLE : Train Time Delay Prediction for High-Speed Train Dispatching Based on Spatio-Temporal Graph Convolutional Network ABSTRACT: Train delay prediction has the potential to improve the quality of train dispatching,
PROJECT TITLE : Spatio-Temporal-Spectral Hierarchical Graph Convolutional Network With Semisupervised Active Learning for Patient-Specific Seizure Prediction ABSTRACT: At the moment, one of the most cutting-edge approaches for

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry