Projekt u sklopu predmeta Analiza slika u biomedicini
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Updated
May 19, 2024 - Jupyter Notebook
Projekt u sklopu predmeta Analiza slika u biomedicini
This code includes classification and detection tasks in Computer Vision, and semantic segmentation task will be added later.
A comprehensive study evaluating 10 CNN image classification models for optimal performance in medical image recognition.
Automated Wildlife Monitoring Using Deep Learning
This application is designed to detect and estimate the calorie content of various foods using GoogleNet, a pre-trained convolutional neural network (CNN). The model has been trained on over 100 different types of foods and can accurately identify and estimate the calories present in those foods based on input images.
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
Алгоритмы Data Science и их практическая реализация на Python
MATLAB code for generating adversarial images using GoogLeNet to test the robustness of deep learning models. Features both untargeted and targeted adversarial attacks.
까먹으면 다시 보려고 정리합니다.
Classification code for AlexNet, VGG, GoogLeNet, ResNet and DenseNet
Implementation of GoogLeNet series Algorithm
Modern deep convolutional neural networks implemented with PyTorch <3. ResNet, DenseNet and InceptionNet are trained on the CIFAR-10 dataset and the results are compared.
This repository is based on the lecture '딥러닝 기반의 영상 인식 모델 구현'
This GitHub repository aims to provide comprehensive overview of the evolution of GoogLeNet, a popular Convolutional Neural Network architecture developed by Researchers at Google for image classification tasks.
Comparative Analysis of SOTA Vision Architectures; VGG, GoogleNet, ResNet & Vision Transformers.
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