Implementation of Dilated VGG Networks for Image Classification task
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Updated
Sep 19, 2020 - Jupyter Notebook
Implementation of Dilated VGG Networks for Image Classification task
Keras implementation of influential CNN architectures.
This repository contains coding files that will help us determine which CNN model architecture performs best at classifying a dog and its various breeds. This project was completed as part of AI Programming with Python Nanodegree program (Udacity).
This was just a project regarding the basics of deep learning. And it has covered most of the basics needed to get an idea regarding hyperparameter tuning, different CNN architecture etc.
Kaggle project keymap to GitHub based on Data Science.
Implementation of Dilated Residual Networks for Image Classification task
This folder contains my reading notes on different topics in Machine Learning.
Driver's Drowsiness Prediction Using CNN Architechtures
Advanced concepts in computer vision, covering topics such as image classification, object detection, and transfer learning techniques for enhanced model performance and accuracy.
[Unmaintained] Notes and implementations of some papers that I had read 📄
Different CNN Architectures for Medical Image Segmentation task
Complete introduction to deep learning with various architechtures. Maths involved is also included. Code samples for building architechtures is included using keras. This repo also includes implementation of Logical functions AND, OR, XOR.
The goal of this project is to study and implement VGG19 based classification model for Flowers' dataset.
Different CNN Architectures for Image Classification task
Deliverables relating to the Advanced Computer Vision for AI University Unit
This research introduces PotatoGANs, a novel data augmentation technique using GANs to generate synthetic potato disease images, improving model generalization in agricultural disease segmentation
Repo for the paper "Deep Multimodal Transfer-Learned Regression in Data-Poor Domains"
Malaria-Detection-Using-CNN
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