Jupyter notebook showing how to build an image classifier with Python and Tensorflow

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Deep Learning: Image classification, feature visualization and transfer learning with Keras

I will share about Machine Learning and Deep Learning.

To Detect and Classify Brain Tumors using CNN and ANN as an asset of Deep Learning and to examine the position of the tumor.

Official PyTorch implementation of "Visualizing the Decision-making Process in Deep Neural Decision Forest", CVPR 2019 Workshops on Explainable AI

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The example of running Image Classification using Core ML

Skin Lesion Analysis Towards Melanoma Detection

The following parameters have been analysed for a short badminton singles match video: 1. Player1 and Player 2 are detected with bounding boxes, 2. Recording and displaying the Start time and end time of the match, 3. Displaying the number of hits made by each player , 4. Displaying the number of out of the boundary hits (AWAYs) made by each player during the course of match, 5. Shuttlecock is detected in every frame of the video with a bounding box.

This repository consists of our Final Year Project. You can find everything starting from our code to all the resources in this repository

Using detectron2 to train Image classification models for backbone of detection models

A novel approach in training a DenseNet model for diagnosing COVID-19 Chest X-Rays.

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Deploying Android application for image classification

MobileNet for Image Classification

Classification of brain tumor in MR images using deep spatiospatial models.

WasteEasy is an app designed to streamline waste management. Developed during the Envision Hackathon, it focuses on waste classification and encourages proper waste segregation. Users can earn points or coupons by utilizing WasteEasy for their waste disposal needs.

Image Classification using Azure Machine Learning workbench

Active Learning for Multiclass Image Classification on Fruits360 Dataset

使用 Vision 和 Core ML 的图像分类器

Deploying Android application for object detection

Code for ImageClassification based on Pytorch

General Image Classification Code base

This Problem is based on a Image Data set consisting of different types of weeds, to detect them in crops and fields. I have used Deep Learning Model called CNN(Convolutional Neural Networks) with Dropout, Batch Normalization, ReduceLearning rate on plateau, Early stoppig rounds, and Transposd Convolutional Neural Networks.

This project related to road safety. We have to wear a helmet according to road safety rules when riding a motorcycle. Therefore, these rules are monitored by the police. Also, Due to the invention of high-quality cameras and the development of the state of art in AI, the surveillance system willing to use AI system to detect whether passengers are wearing helmets or not. In this category I have built a model, first, it can be able to detect the motorcycle, then it will find out who is riding the bike. Finally, it will determine whether the person is wearing a helmet or not. To that end, I trained the pre-trained model SSD-MobileNet-V1 to detect motorcycles and humans.

Build a image classification python web app with Streamlit and PyTorch :cat: :dog:

Deploy an Image classification website with Ngrok

Aplikasi deteksi penyakit kulit menggunakan AI. Dibuat untuk menyelesaikan Tugas Akhir AI Mastery Program Orbit Future Academy X SIB Kampus Merdeka 2022.

Models for Computer Vision