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K-Means Clustering for Image Classification Using OpenCV

Machine Learning Mastery

In a previous tutorial, we have explored the use of the k-means clustering algorithm as an unsupervised machine learning technique that seeks to group similar data into distinct clusters, to uncover patterns in the data.

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Deploying a Custom Image Classifier on an OAK-D

PyImageSearch

Home Table of Contents Deploying a Custom Image Classifier on an OAK-D Introduction Configuring Your Development Environment Having Problems Configuring Your Development Environment? The converted blob file would then run image classification inference on the OAK-D using the DepthAI API.

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70+ Best and Unique Python Machine Learning Projects with source code [2023]

Mlearning.ai

This project uses various advanced techniques like CNNs, VGGs, XGBoost, etc for performing 7 disease detections. Doctor-Patient Appointment System in Python using Flask Hey guys, in this blog we will see a Doctor-Patient Appointment System for Hospitals built in Python using Flask. It is going to be a very interesting project.

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Introduction to Autoencoders

Flipboard

Dimensionality Reduction Feature Learning Anomaly Detection Denoising Images Image Inpainting Generative Modeling Recommender Systems Sequence-to-Sequence Learning Image Segmentation How Are Autoencoders Different from GANs? An autoencoder is an artificial neural network used for unsupervised learning tasks (i.e.,

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Training the YOLOv8 Object Detector for OAK-D

PyImageSearch

one , two , three , four , and five ) with good mean average precision (mAP). Furthermore, since this tutorial acts as a strong base for an upcoming tutorial, the trained YOLOv8 variant should be able to run inference in near real-time on the OpenCV AI Kit (OAK) that comes powered with the Intel MyriadX neural hardware accelerator.