Large-Scale Multi-Class Image-Based Cell Classification with Deep Learning

It is a Flask Application to predict a person covid positive/negetive based on chest x ray of a person.This Machine Learning Web Application utilizes a Two-Layered Convolutional Neural Network to process the chest-x-ray Images and predict if they are corona positive/negetive accuracy of nearly 81%.

Dog Breed Classifier Project-Deep Learning Nanodegree Udacity

Derin Öğrenme kullanarak el yazısıyla yazılmış rakamları tanımak için yazılmış bir Flask uygulamasıdır.

MAT-CNN-SOPC: Motionless Analysis of Traffic Using Convolutional Neural Networks on System-On-a-Programmable-Chip

Sign Language Detection Using CNN

Pediatric pneumonia image classification with (strongly) imbalanced data via Pytorch 🫁

Industrial Motor Fault Detection System using a 1D-CNN with TensorFlow, SciPy, SKLearn, Numpy, Pandas. End-To-End classification from raw vibrational signals reducing computational overhead and faster inference times. Transfer learning implementation demonstrating promise for real world industrial applications.

A machine learning website created using Django.You can test our models of Cnn,Gans.etc.and see them working in real time.

A Diagnostics system to help doctors detect early symptoms of Melanoma | CNN | Python | Flask

A full-stack flask web application that lets users draw doodles and classify them using a CNN trained on a subset of the Quick, Draw! dataset.

Cotton disease detection using CNN

Diagnosing colorectal cancer from histopathology images using deep learning: final project code.

Final Thesis Dissertation in Fulfillment of our Bachelor of Science in Engineering (B.Sc.Engg) with major in Computer Science and Engineering. This research is entitled *Optimized Human-Emotion Detection in Written-Text using Hybrid Machine Learning Classification Algorithm*, with codename *OEHML* Framework.

Cat-Dog Image Classifier using CNN, Deployed with Flask on Heroku

Flask app for Classification of Dog/Cat using (CNN) with transfer learning @MobileNetV2

Image colorization is a challenging task and a topic of ongoing research in the area of Computer Vision. We present a convolutional-neural-network-based system that faithfully colorizes black and white photographic images without direct human assistance. We explore various network architectures, objectives, color spaces, and problem formulations…

Coursera Course

It is an app that do calculation like Multiplication, Addition, Division and Subtraction using Digit Recognition Model(i.e. trained with help of CNN).