Artist Identification: comparison between AlexNet, GoogLeNet and ResNeXt
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Updated
Jul 29, 2019 - TeX
Artist Identification: comparison between AlexNet, GoogLeNet and ResNeXt
Funciones utilles para PyTorch.
Trying to code Resnet50 on pytorch and testing it on CIFAR10 dataset
This project is a convolutional neural network (CNN) built using PyTorch that classifies images from the Fashion-MNIST dataset. The network consists of several layers including convolutional layers, pooling layers, and fully connected layers. The model achieved an accuracy of 92.1%
Our novel approach is dedicated to refining image classification using customized CNN Kernel. The primary objective is to enhance algorithmic performance, bolstering adaptability and feature extraction capabilities.
2018-2019 Semester2 at Soton, lab practice for Deep Learning
Audio Explorers Electrical Challenge 1, "Sound scene classifier for hearing aids" created by Team AudioBots.
Profile Face Recognition project
Transforming 2D images into 3D semantically segmented scenes using innovative CNN architecture and COLMAP reconstruction.
A Method to Improve Any ECG Denoising Technique In limb leads
Transfer Learning to Classify CIFAR-100 images
Step by step approach to build Convolution Neural Network as per State of the Art Model.
Dissertation completed for the award of MSci in Computer Science. This dissertation is about automated breast cancer detection in low-resolution whole-slide pathology images using a deep convolutional neural network pipeline.
Project consists of age and gender classification based on faces images (200x200).
This repository contains the code and results for a CIFAR10 image classification project using a custom ResNet34 model.
Trains convo neural network, converts to onnx, infer in Unity with Sentis NN
Implementation of Machine Leaning Algorithms
Simple convolution neural network to classify handwirtten digits of MNIST dataset
MNIST classification and visualize class activation maps with Pytorch.
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