Scene Analysis based on Feature Extraction and Deep Learning

Scene classification relies on images and is essential in many computer vision applications. The scientific interest in scene classification from remotely collected images is increasing, and many datasets and algorithms are being developed. The introduction of convolutional neural networks (CNN) and

Project Title

Scene Analysis based on Feature Extraction and Deep Learning

Project Area of Specialization

Software Engineering

Project Summary

Scene classification relies on images and is essential in many computer vision applications. The scientific interest in scene classification from remotely collected images is increasing, and many datasets and algorithms are being developed. The introduction of convolutional neural networks (CNN) and other deep learning techniques contributed to vast improvements in the accuracy of image scene classification in such systems. In this project , we will apply feature extraction from various neural networks for an efficient and reliable image classification system with some applications relevant to remote sensing of scene classification. 

Project Objectives

we will research on image classification usinng CNN  modern techniques ,  reimplement  alreaady developed aggorithms developed in CNN  techniques  to make high  accuracy ,  performace , efficiency and after it implement it into Android app for  Practcal use. Our project  bring improement in soo many areas like agriculture, AI , machine laerning, image recongnition, security , object detection, segmentation , self driving cars and robotics and many other fields .

Project Implementation Method

We will use matlab  and  anaconda using paython to develop  the project and  aslo implement  in android App.

Benefits of the Project

High accuracy in image classification ,  performance and efficiency. our project goal is not specific , as image classification in many recent areas like,  

Google Image Search 
Car License Plate Recognition by camera( to detect car owner & send him Speeding ticket on his address)

Face Recognition & Iris Recognition in Mobile Security & building doors security
Real Emotion detection system detection system to analyze how they are feeling when they are hospitalized
Biometrics Recognition is the simplest example of image recognition which scans the print of thumb & remembers the print algorithim in database.
Pedestrian Brake system alert in cars to recognize the object as a person and stop the car at a safe distance thus by saving the person from a major accident.
Recognizing People images in gallery to seperate them & view only their pics( Found mostly in IOS Devices)

our improvement bring changes in All  fields related to image classifation

Technical Details of Final Deliverable

firsty we  reimplement the CNN model for better  scene analysis  integrate code in  android app , upload  on play store and then we will publish our research  paper on image classification

Final Deliverable of the Project

Software System

Core Industry

Others

Other Industries

Education , IT , Medical , Agriculture , Food , Media , Security , Telecommunication

Core Technology

Artificial Intelligence(AI)

Other Technologies

Augmented & Virtual Reality, Robotics, NeuroTech

Sustainable Development Goals

Quality Education, Decent Work and Economic Growth, Industry, Innovation and Infrastructure, Life on Land

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com