multiclass-image-classification
There are 100 repositories under multiclass-image-classification topic.
vijayg15/Keras-MultiClass-Image-Classification
Multiclass image classification using Convolutional Neural Network
MuhammedBuyukkinaci/TensorFlow-Multiclass-Image-Classification-using-CNN-s
Balanced Multiclass Image Classification with TensorFlow on Python.
France1/unet-multiclass-pytorch
Multiclass semantic segmentation using U-Net architecture combined with strong image augmentation
teja0508/BCS_Body_Condition_Score_Cattle_Prediction
body-condition-score_cattle prediction.
VishalShah1999/MultiClass-Image-Classification
This will help you to classify images into Multiple Classes using Keras and CNN
Amaan-developpeur/fundus-image-disease-classification
Deep learning pipeline for classification of Cataract, Diabetic Retinopathy, Glaucoma and Normal using fundus images
deepankarvarma/Handwriting-Recognition--OpenCV--Keras-and-TensorFLow
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.
kaustubhbhavsar/animals-10-classification
Multiclass Classification of Imbalanced Image Dataset using Transfer Learning.
neelkantnewra/Multiclass-disease-classification-using-modified-CNN
This repository contains models for Multi-class disease detection using Chest X ray. A detail analysis of our approach is mentioned.
SubhangiSati/Identification-of-Gemstone-using-MobileNetV2-and-transfer-learning
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
IIsameerII/Handwritten-Digit-Recognition-from-MNIST-Dataset
This project uses TinyVGG and Streamlit to classify handwritten digits.
MuhammedBuyukkinaci/My-Jupyter-Files
This repository is containing my Jupyter files.
Nirmala-research/YOLOv7-XAI
Multiclass Skin lesion localization and Detection with YOLOv7-XAI Framework with explainable AI
tahirlee/RCG-Net-convolution-transformer-based-network-for-histopathology-image-classification
Code for "A Novel Convolution Transformer-Based Network for Histopathology Image Classification Using Adaptive Convolution and Dynamic Attention"
AtulJoshi1/image-classification
Multi-class classification by Deep Learning approach on image data.
deepankarvarma/American-Sign-Language-MultiClass-Image-Classification-OpenCV-Keras-TensorFlow
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.
deepankarvarma/Rice-MultiClass-Image-Classification-OpenCV-Keras-Tensorflow
This repository contains Python code for rice type detection using multiclass classification. The project leverages the MobileNetV2 architecture to classify six different types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. The dataset used for training and evaluation can be found on Kaggle and consists of categorized rice images.
Otatoess/HAM-skincancer
This repository contains a deep learning model for skin cancer classification using the InceptionV3 architecture. The model was trained on the HAM10000 dataset and is designed with computational efficiency in mind. It was developed to be able to run on a CPU.
RajkumarGalaxy/birds
Photographs of Birds for Multi-target Images Classification
SayamAlt/Flowers-Recognition
Successfully trained a deep learning model which can precisely predict the species of flowers based on their images.
SubhangiSati/Multi-class-classification-of-Bird-species
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.
thepankj/Image-Classification-Transfer-Learning-Heroku
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.
venkatavamsi01/CNN_VGG19_EfficientNet_Distraction_Detection
Driver Distraction Detection with CNN and Transfer Learning (VGG19, EfficientNet)
wittyicon29/AppleAI--Apple-Disease-Detection-Using-CNN
Apple disease detection using CNN is a GitHub repository that contains code for detecting diseases in apples using convolutional neural networks (CNNs). The repository uses a dataset of images of healthy and diseased apples to train the CNN model. The model is then used to classify new images of apples as healthy or diseased
aevinj/ImageClassifier
Multiclass classification of images of cats, dogs and fish
AjNavneet/CNN-MultiClass-Classification-PyTorch
PyTorch implementation of CNN model for multi-class classification.
anik475/Vission-Transformer-for-Image-Segemntion-using-UNET-R
Implementation of V architecture with Vission Transformer for Image Segemntion Task
apachex692/tensorflow-multiclass-image-classication
Tensorflow Multi-class Image Classification
FionaAmuda/Image-Classification
Multiclass classification using TensorFlow
HansakaDilshanJayawardana/MLAssignment
SLIIT 4th Year 2nd Semester Machine Learning Project
m3mentomor1/Pneumonia_Detection_with_Lightweight-CNN-Models
This is a project focused on identifying the presence of pneumonia in chest X-ray images. Each image can be classified into one of three categories: Bacterial Pneumonia, Viral Pneumonia, or Normal.
nadyanvl/COVID-Multiclass-App
COVID-19 CT scan image classification using EfficientNetB2 with transfer learning and deployment using Streamlit. This project focuses on accurately classifying CT scan images into three categories: COVID-19, Healthy, and Others. Leveraging transfer learning on pretrained EfficientNetB2 models, the classification model achieves robust performance.
rsachintha/Final_Year_Project-Snakes-Things-
This is the project I did as a part of my final year research regarding Multiclass Image Classification. This system identifies snake species relevant to the user uploading an image. A convolutional Neural Network was used to implement the image classification model and deployed using Flask. The model gained more than 80% of accuracy.
ShrirangKanade/Obstacle_Detection_on_Lunar_Surface_using_U-Net
This repository represents a web app with a multi-class classification ML model which creates a segmented image of rocks and plain land.
SunilGolden/DermatoAI-ISIC2018
Skin Lesion Classifier using the ISIC 2018 Task 3 Dataset.
varmatilak22/Food_Vision_App
Food Vision Pro is a Streamlit app built with TensorFlow and CNN architecture, leveraging EfficientNet for deep learning-based food image classification. The model is fine-tuned on the Food101 dataset using mixed precision training and data augmentation techniques to accurately identify food items. It also integrates the NutritionixAPI for fetching