Digital image processing is the use of algorithms to make computers analyze the content of digital images.
Image processing assignments for CS663
The system should utilize state-of-the-art facial recognition algorithms to accurately identify individuals based on their unique facial features. Advanced machine learning models should enable the system to adapt to diverse scenarios, including varying lighting conditions, facial expressions, poses, and occlusions, ensuring reliable and precisely.
i am learning AI/ML and this performing this collage assignments.
Course Assignments for CS663 - Digital Image Processing
Implementation of algorithms learnt as part of Digital Image Processing Course
Digital-Image Processing projects with opencv 2019.1
This repository showcases a virtual tour of a Sacred Heart University classroom using Matterport technology. It includes an interactive 3D model embedded in a single HTML page, demonstrating responsive web design, smooth navigation, and a professional layout to provide an immersive user experience.
A project on learning digital image processing through an interactive medium. Also on: https://pixelpit.netlify.app/
-This repo is meant to supplement practical lessons in Digital Image Processing (DIP)/Analysis (DIA).
Assignments for CS663, IIT Bombay, Autumn 2018
Learn Digital Image Processing Using MATLAB
Repository for assignments in Digital Image Processing (CS663), IIT Bombay (Autumn 2017)
Repository containing our solutions for CS663'course Assignments
RetroSpectra is a real-time facial emotion detection application. It uses Convolutional Neural Network (CNN) to identify human emotions from live video feed. The application leverages a pre-trained model to accurately detect and classify emotions, providing an interactive and engaging user experience.
Digital Image Processing coursework (Sharif University of technology)
Assignment Codes for CS663 Digital Image Processing
课件：数字图像处理，深度学习，计算机视觉，机器学习