This repo is for Image Classification of butterfly images of 10 classes using Transfer Learning. Different Pre-trained DL models were used for Transfer Learning. Also, flask was used to create a front end.
DiNeSys is a distributed system built for deep learning network profiling on cloud-edge systems, developed with Tensorflow (CNN computational part) Apache Thrift (client/server structure)
Specific image manipulations and inference with openCV, VGG19, ResNet50 with a simple UI.
Brain Tumor Detection Project with HaarCascade, Convolution Neural Network and OpenCV
This project about transfer learning with cnn
A comprehensive collection of PyTorch implementations for the VGG (Visual Geometry Group) models
A comparative analysis of deep learning algorithms for multi label image classification using microscopic images.
This project consists of a web application built with React for the frontend and Flask for the backend. The application allows users to perform neural style transfer on images, where the style of one image is applied to the content of another image to generate visually appealing results.
Transforming agriculture with AI: Explore our GitHub for advanced plant disease detection. Utilizing top CNN models, we empower farmers with early diagnosis tools. Access notebooks, datasets, and a user-friendly web app. Join us in revolutionizing farming for a sustainable future
Click the link below to checkout the website
📖 Paper: A Neural Algorithm of Artistic Style 🖼️
Implementation and results from "Beyond GOTEX: Using Multiple Feature Detectors for Better Texture Synthesis"
VGG19 --> Neural Style Transfer
Dream Image Generation Project
WE WILL BE CLASSIFYING WHETHER THE PERSON HAS MALARIA OR NOT BY CLASSIFYING THE X-RAY SCANS OF INFECTED AND UNINFECTED IMAGES.
This repository houses my assignments completed during the Deep Learning course as part of my Master's in Data Analytics program. Explore diverse projects showcasing hands-on applications of advanced neural networks and machine learning techniques.
a robust method of classification and recognition of coffee leaf diseases using both classical ma learning and deep learning methods, also a custom CNN. These methods were evaluated on the Arabica coffee leaf dataset known as JMuBEN.
Trí tuệ nhân tạo, mạng học sâu Inception V3, VGG19, DenseNet 121 và Unet trong việc phát hiện và khoanh vùng nhiễm bệnh Covid 19 từ ảnh chụp phổi
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