This project utilizes the LeNet CNN architecture to classify traffic signs from a dataset of 32x32 pixel images
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Updated
Sep 4, 2024 - Jupyter Notebook
This project utilizes the LeNet CNN architecture to classify traffic signs from a dataset of 32x32 pixel images
Facial Recognition and Emotion detection project with focus on hyperparameter tuning
This model develops an accurate system for classifying retinal images to assist in early detection and management of eye conditions.
This is an implementation of the LeNet-5 architecture on the Cifar10 and MNIST datasets.
This repository is a compilation of machine learning algorithms implemented by me on differnet datasets and I'm currently working on it. The algorithms are categorized based on the types of data they are designed to handle and some of the codes are just a basic descriptions about the algorithms.
Pytorch Tutorial & Deep Learning Different architecture
The Deep Learning Concepts Repository is a concise and accessible collection of essential concepts in deep learning. It provides clear explanations and examples for neural networks, CNNs, RNNs, activation functions, loss functions, backpropagation, gradient descent, and overfitting/underfitting. An invaluable resource for beginners and practitioner
This repository is a collection of PyTorch code examples, covering beginner to advanced topics, and including implementation of CNN models from scratch.
This project utilizes a convolutional network to identify 9 different kinds of skin cancers including melanoma, nevus, and more. The model is trained on over 2,200 pictures of various skin cancers based off of this dataset. This model implements fundamental computer vision and classification techniques and includes a step-by-step implementation.
This is a machine learning project where I utilized the LeNet-5 architecture to create a convolutional deep network that classifies 43 different kind of traffic signs. I've made sure to include a full step-by-step implementation of the project as well as detailed notes for every step.
Batch normalization from scratch on LeNet using tensorflow.keras on mnist dataset. The goal is to learn and characterize batch normalization's impact on the NN performance.
Building & Deploying Computer Vision Models
Different CNN architecture like LeNet, AlexNet,VGGNet,Inception,Resnet is included in this repo
Lenet customisation with more filters, 3*3 filters, Relu activation fucntion
In this project we make use of convolutional neural network to recognise digits from 0 to 9. The neural network architecture used in this project is LENET-5.
Implementation of LeNet-5 over MNIST Dataset using PyTorch from Scratch, presenting an accuracy of ~99%
Disease identification using keras and LeNet.
This assignment is class assignment 5 for the visual analytics class at Aarhus University, 2021.
I am working on implementing Machine Learning Algorithms from scratch.
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