Multiclass image classification using Convolutional Neural Network

Balanced Multiclass Image Classification with TensorFlow on Python.

Multiclass semantic segmentation using U-Net architecture combined with strong image augmentation

body-condition-score_cattle prediction.

This will help you to classify images into Multiple Classes using Keras and CNN

Binary or multi-class image classification using VGG16

This repository is containing my Jupyter files.

This repository contains Python code for handwritten recognition using OpenCV, Keras, TensorFlow, and the ResNet architecture. The project utilizes two datasets: the standard MNIST 0-9 dataset and the Kaggle A-Z dataset. The OCR model is trained using Keras and TensorFlow, while OpenCV is used for image pre-processing.

This repository contains models for Multi-class disease detection using Chest X ray. A detail analysis of our approach is mentioned.

This project uses TinyVGG and Streamlit to classify handwritten digits.

Multi-class classification by Deep Learning approach on image data.

This repository contains Python code for a project that performs American Sign Language (ASL) detection using multiclass classification. It utilizes YOLO (You Only Look Once) and MobileNetSSD_deploy for object detection, achieving an accuracy of 91%. The code offers options to predict signs from both images and videos.

Multiclass Classification of Imbalanced Image Dataset using Transfer Learning.

Photographs of Birds for Multi-target Images Classification

The project focuses on Identification of various Gemstone. The dataset consists of 87 classes.It shows the whole progress and model used to achieve final accuracy. You will gain knowledge of Computer Vision, The model used are CNN(Convolutional Neural Network), MobileNetV2 and VGGNet,The final model used was transfer learning with model MobileNetV2

A multiclass image classification project, used transfer learning to use pre-trained models such as InceptionNet to classify images of butterflies into one of 50 different species.

SLIIT 4th Year 2nd Semester Machine Learning Project

Binary or Multi Classifier to classify images by using Deep learning Architecture.

This repository represents a web app with a multi-class classification ML model which creates a segmented image of rocks and plain land.

The Bird Species Classifier is an application built using a Convolutional Neural Network (CNN) to classify images of birds into one of 525 different species. It allows users to upload an image of a bird and receive a prediction of the bird species. Along with analysing the performance of various optimising algorithms.