Feature Detection

Introduction to Feature Matching Using Neural Networks

Feature matching using deep learning is a game-changer for computer vision tasks like panorama stitching, video stabilization, and face recognition, providing greater accuracy and reliability. Dive into how this technology

Computer Vision, Deep Learning, Feature Detection, Neural Network

t-SNE: T-Distributed Stochastic Neighbor Embedding Explained

t-SNE (t-Distributed Stochastic Neighbor Embedding) is a dimensionality reduction techniques used to vizualize data. Continue reading to know more.

Deep Learning, Feature Detection, Machine Learning, Tensorflow, Tensorflow Tutorials

Otsu’s Thresholding with OpenCV

In this post, we will examine Otsu’s method for automatic image thresholding. What is Image Thresholding? Image thresholding is used to binarize the image based on pixel intensities. The input

Feature Detection, OpenCV 4, Segmentation, Tutorial

CNN Receptive Field Computation Using Backprop with TensorFlow

In our recent post about receptive field computation, we examined the concept of receptive fields using PyTorch. We learned receptive field is the proper tool to understand what the network

Deep Learning, Feature Detection, Image Classification, Keras, Object Detection, Tensorflow, Tutorial

CNN Fully Convolutional Image Classification (FCN CNN) with TensorFlow –

In a previous post, we covered the concept of fully convolutional neural networks (FCN) in PyTorch, where we showed how we could solve the classification task using the input image

Deep Learning, Feature Detection, Image Classification, Image Processing, Keras, Object Detection, Tensorflow

Faster R-CNN Object Detection with PyTorch

1. Image Classification vs. Object Detection Image Classification is a problem where we assign a class label to an input image. For example, given an input image of a cat,

Courses, Deep Learning, Feature Detection, Getting Started with PyTorch, Machine Learning, Object Detection, OpenCV 3, PyTorch, Segmentation, Tracking, Tutorial