Say Hello to Artificial Intelligence
Say Hello to Artificial Intelligence
Dimensionality reduction is a method used to reduce the number of features or dimensions in a dataset. This is often done to reduce the complexity of the data, make it easier to visualize, or to improve the performance of machine learning algorithms. There are many different techniques for dimensionality reduction, including: Dimensionality reduction can be …
Morphological operations are a set of image processing operations that are performed on binary images. These operations are based on the shape of the objects in the image, and are used to extract structural information from the image. Some common morphological operations include dilation, erosion, opening, closing, and skeletonization. These operations can be used to …
Image classification is the process of assigning a label or category to an image based on its visual content. It is a common task in computer vision, and there are many algorithms and models that can be used to perform image classification. Convolutional Neural Networks (CNNs) are a type of deep learning model that are …
A convolutional neural network (CNN) is a type of deep learning model that is commonly used for image classification and other tasks that involve analyzing visual data. CNNs are composed of multiple layers, including convolutional layers, pooling layers, and fully connected layers. The convolutional layers of a CNN are responsible for extracting features from the …
As I mentioned in my previous blog, face mask detection uses deep learning techniques. In this blog, you will learn how to accurately detect the face mask and classify it into two categories (face mask and no face mask). For this purpose, first, we trained the deep learning CNN model (MOBILE NET) using the facemask …
Facemask detection using deep learning techniques. In this blog, you will learn how to accurately detect the face mask and classify it into two classes (face mask and no face mask). For this purpose First, we trained the deep learning CNN model(Resnet) using the facemask dataset. After training the model, we used that model with …
Fashion-MNIST is a dataset of Zalando’s article images, consisting of a training set of 60,000 examples and atest set of 10,000 examples. Each example is a 28×28 grayscale image, associated with a label from 10classes.Each training and test example is assigned to one of the following labels: T-shirt/top, trousers, Pullover,Dress, Coat, Sandal, Shirt, Sneaker, Bag, …
Computer Vision is one powerful tool that helps in predicting various tasks.In this blog, you will learn how to measure the distance between a person and a camera. step 1 download the Haarcasde classifier to detect faces in real-time (haarcascade_frontalface_default.xml). https://github.com/kipr/opencv/tree/master/data/haarcascades Code:
Text extraction, often known as keyword extraction, is a method of automatically scanning text and extracting relevant or core words and phrases from unstructured data such as news articles, surveys, and customer service issues using machine learning. In this blog, we will see how we can extract text by using pytesseract library. First, need to …
In this blog, we learn how to diagnosis the prediction of X-rays knee classification using Convolutional neural network and then deploy the model using Web-based Flask application. Diagnosis for the prediction of knee osteoarthritis using deep learning techniques. The dataset consists of 1650 digital X-ray images of knee joint which are collected from well reputed …
Diagnosis for prediction of knee osteoarthritis using deep learning Read More »