GitHub topics: multiclass-image-classification

Repositories

MuhammedBuyukkinaci/TensorFlow-Multiclass-Image-Classification-using-CNN-s

Balanced Multiclass Image Classification with TensorFlow on Python.

Language: Python - Size: 144 MB - Last synced at: 15 days ago - Pushed at: over 2 years ago - Stars: 71 - Forks: 38

apachex692/tensorflow-multiclass-image-classication

Tensorflow Multi-class Image Classification

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nikolaos-mavromatis/cifar-10-image-classification

Language: Jupyter Notebook - Size: 237 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

MyriamBA/Face-Mask-Detection-Computer-Vision

A Multiclass Object Detection project for face mask detection.

Language: Jupyter Notebook - Size: 618 MB - Last synced at: about 1 month ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

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

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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.

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aayamrajshakya/Campus_Vision_AI_challenge

Campus building classification (Competition held by MSU SIG AI Club)

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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

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IsraelAzoulay/food-image-101-classes-classifier-computer-vision

Computer vision deep learning project classifying 101 classes of food images with 80% accuracy, built with TensorFlow. Beats the baseline accuracy of 50.76% (Food101 paper) and 77.4% (DeepFood paper).

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IsraelAzoulay/food-image-deca-classifier-computer-vision

Computer vision deep learning project classifying 10 classes of food images with 90% accuracy, built with TensorFlow.

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Nirmala-research/YOLOv7-XAI

Multiclass Skin lesion localization and Detection with YOLOv7-XAI Framework with explainable AI

Language: Python - Size: 1.59 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

Mrudula1205/CoffeeBeanRoastClassification

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ItzAmeerHamza/pededstrian-classification-using-multiclass-classification

Multiclass classification using Feature Fusion and Support Vector Machine

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mhizterpaul/e-commerce_clothing_classifier

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Manohara-Ai/Hand_Written_Digit_Recognizer

Building a CNN to identify hand written digits

Language: Python - Size: 101 KB - Last synced at: 22 days ago - Pushed at: 4 months ago - Stars: 4 - Forks: 0

jotstolu/Multiclass-image-classification-Rice-leaf-Disease-Dataset

The focus of this project is to develop and evaluate six distinct machine learning models for multi-class classification of Rice Leaf Diseases images. This multi-class classification task involves 1)Image Preparation and Pre-processing 2)Feature Extraction 3)Model Training and hyperparameter tuning 4)Model Evaluation and Analysis

Language: Jupyter Notebook - Size: 192 KB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

shihjen/CNN_Ocular_Disorders_OCT

A deep learning project focuses on classifying ocular disorders using Optical Coherence Tomography (OCT) images. By leveraging the EfficientNetV2 architecture, the project develops models that effectively identify various ocular conditions, achieving accuracies exceeding 90%.

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SayamAlt/Flowers-Recognition

Successfully trained a deep learning model which can precisely predict the species of flowers based on their images.

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shihjen/CNN_Ocular_Disorders

A deep learning-based classification system achieving 94% accuracy in distinguishing between diabetic retinopathy, glaucoma, and cataracts from normal eye images using fundus photography.

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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"

Language: Python - Size: 120 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

EMCL-Research-ITSecLab/ssci23-xai-network-traffic

SSCI23 Explainable AI in Network Traffic Classification

Language: Python - Size: 13.2 MB - Last synced at: about 1 month ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

Dharundp6/Indian_Bovine

The Indian Bovine Classification project is an innovative web application designed to revolutionize the identification and study of Indian cattle breeds. Combining state-of-the-art image recognition technology with an intelligent chatbot system, this tool offers a comprehensive solution for classifying and learning about various Indian bovine breed

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4ritam/Leaf-Disease-Classification

Leaf Disease multi-class image classification using deep learning architectures implemented in PyTorch

Language: Python - Size: 364 MB - Last synced at: 8 months ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

vijayg15/Keras-MultiClass-Image-Classification

Multiclass image classification using Convolutional Neural Network

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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.

Language: Python - Size: 353 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 2 - Forks: 1

anik475/Vission-Transformer-for-Image-Segemntion-using-UNET-R

Implementation of V architecture with Vission Transformer for Image Segemntion Task

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Hadley-Dixon/DigitRecognizer

Basic classification algorithm for the MNIST dataset that uses computer vision fundamentals including simple NNs

Language: Python - Size: 85 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

Hasnat-Aarif-Aslam/Hand-Written-Digit-Classification-MNIST-Multi-Class-Classification

This repository demonstrates a TensorFlow/Keras model for classifying MNIST handwritten digits. It covers data loading, normalization, model creation, training with early stopping, and evaluation. Includes visualizations of loss and accuracy over epochs and explains image shape considerations for predictions.

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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.

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ahadpaksoy/MulticlassClassifierWCifar100

Trained a multiclass classifer network using cifar100 dataset

Language: Python - Size: 10.7 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

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.

Language: Python - Size: 42.5 MB - Last synced at: 12 months ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

heiwan-bangkit-project/ml-heiwan-tfmodels

Notebooks of our modeling process for Multiclass Classifications at around 158 different Cats, Dogs, and Bird breeds.

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SunilGolden/DermatoAI-ISIC2018

Skin Lesion Classifier using the ISIC 2018 Task 3 Dataset.

Language: Python - Size: 33.2 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

omkar3060/A-Multiclass-Classifier-for-Lung-Cancer-Diagnosis-Using-Resnet50

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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.

Language: Python - Size: 1.81 MB - Last synced at: 12 months ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

jayakumarpujar/Image-Classifier

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

Language: Python - Size: 9.77 KB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

RimTouny/Image-Classification-using-Chars74K-dataset

Employing advanced techniques, the project seamlessly integrates binary and multiclass classifiers for character classification. It offers a comprehensive analysis and adeptly addresses challenges in the realm of computer vision.This project was part of my uOttawa Master's in Computer Vision course (2023).

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AjNavneet/CNN_MultiClass_Classification_PyTorch

PyTorch implementation of CNN model for multi-class classification.

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AjNavneet/SequentialCNN_MultiClassClassification_TensorFlow

Sequential CNN model using tensorflow for multi-class classification on images.

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makmary/Skoltech-ML-2022-Drone-Collision-Avoidance-In-Indoor-Environment

Obstacle and free-space detection system for drones

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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.

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venkatavamsi01/CNN_VGG19_EfficientNet_Distraction_Detection

Driver Distraction Detection with CNN and Transfer Learning (VGG19, EfficientNet)

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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.

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France1/unet-multiclass-pytorch

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

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sibap865/car_classification_using_cnn

Ths project explains how a bigener can use simple convolutional neural network (cnn) to classify car images

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yvesyue/landmark_classifier

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jyotsnayall/Sign-Language-Detection

Convolutional Neural Network(CNN) using Python and Keras to classify American Sign Language (ASL) alphabet hand signs.

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alekswael/fruit_classifier_LR_VGG16

This repo contains code for conducting image classification on a dataset of fruit images. Two models are fit to the data; a simple sequential model which is akin to multiclass logistic regression, and a large pretrained CNN model (VGG16).

Language: Python - Size: 77.4 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

aevinj/ImageClassifier

Multiclass classification of images of cats, dogs and fish

Language: Python - Size: 914 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

VishalShah1999/MultiClass-Image-Classification

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

Language: Python - Size: 168 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 7 - Forks: 1

Naimul-Islam-Siam/Dog-Vision

This is an end to end deep learning multiclass image classifier project built using TensorFlow.

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IIsameerII/Handwritten-Digit-Recognition-from-MNIST-Dataset

This project uses TinyVGG and Streamlit to classify handwritten digits.

Language: Python - Size: 9.79 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

ValantisAndreas/OxML-Carcinoma-CLF

This project was part of the MLx Cases section of the OxML 2023 summer school.

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justashu/Image-Classifier-MNSIT-Dataset-

- Built a deep learning model from scratch, used the mathematical equations to implement algorithms in the model

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rainaa0277/Fashion-MNIST-Classifier-using-ANN

Fashion training set consist of 70,000 images divided into 60,000 training and 10,000 testing samples. Dataset samples consists of 28x28 grayscale image associated with a label from 10 calsses.

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kattat13/PL-traffic-signs-predict

Predict polish traffic signs

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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.

Language: Python - Size: 18.6 KB - Last synced at: 12 months ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 1

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.

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teja0508/BCS_Body_Condition_Score_Cattle_Prediction

body-condition-score_cattle prediction.

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HansakaDilshanJayawardana/MLAssignment

SLIIT 4th Year 2nd Semester Machine Learning Project

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kaledhoshme123/Classification-foliar-diseases-in-apple-trees-with-accuracy-99-

Misdiagnosis of many diseases affecting agricultural crops can lead to chemical misuse resulting in the emergence of resistant pathogenic strains, increased input costs, and more outbreaks leading to significant economic losses and environmental impacts. A structure of a convolutional neural network has been proposed that is capable of diagnosing disease in apple plant leaves. The proposed neural network structure was able to reach an accuracy of more than 99 percent.

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