Heatmap Visualization of a Image Classification Model like Xception using GRAD-CAM #880
Description
Deep Learning Simplified Repository (Prop.osing new issue)
🔴 Project Title : Heatmap Visualization of a Image Classification Model like Xception using GRAD-CAM
🔴 Aim : GRAD-CAM, which stands for Gradient-weighted Class Activation Mapping, is a technique used in the field of computer vision to visualize the regions of an image that are important for a convolutional neural network's decision-making process.So I would like to use Deep learning techniques like GRAD-CAM to explain why the Xception model is classifying that as an "Persian cat" ( Or anything else ) visually through a heatmap.
🔴 Dataset : Not applicable as I will be using an Xception model with the imagenet weights to explain the reson it classified that as that using GRAD CAM
🔴 Approach : Since ML techniques like CNN are essentially "Black Boxes", it is hard for us to understand why it made that choice. Using GRAD-CAM we are able to explain why the CNN model made that particular choice that it did. It helps us to visually understand the "why" of the classification.
📍 Follow the Guidelines to Contribute in the Project :
- You need to create a separate folder named as the Project Title.
- Inside that folder, there will be four main components.
- Images - To store the required images.
- Dataset - To store the dataset or, information/source about the dataset.
- Model - To store the machine learning model you've created using the dataset.
requirements.txt- This file will contain the required packages/libraries to run the project in other machines.
- Inside the
Modelfolder, theREADME.mdfile must be filled up properly, with proper visualizations and conclusions.
🔴🟡 Points to Note :
- The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
- "Issue Title" and "PR Title should be the same. Include issue number along with it.
- Follow Contributing Guidelines & Code of Conduct before start Contributing.
✅ To be Mentioned while taking the issue :
- Full name : Abhijith M S
- GitHub Profile Link : https://github.com/AMS003010
- Email ID : abhijithmsaji132@gmail.com
- Participant ID (if applicable):
- Approach for this Project : Implementation, Code and Results will be provided
- What is your participant role: GSSOC'24
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎