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Category upArtificial Intelligence

Computer Vision

Computer Vision is a specialty in Artificial Intelligence that focuses on how computers can interpret images. Learn about some of the core concepts through our tutorials.

  • Neural Networks (18)
  • Object Detection (7)
  • Convolutional Neural Networks (5)
  • Training (2)
  • Generative Adversarial Networks (2)

>> How Does Face Recognition Work?

>> Optical Flow: Lucas-Kanade Method

>> What Is Gradient Orientation and Gradient Magnitude?

>> What Are Contours in Computer Vision?

>> What Is the Purpose of a Feature Map in a Convolutional Neural Network

>> How Does a Neural Network Recognize Images?

>> 2D Convolution as a Matrix-Matrix Multiplication

>> Introduction to Landmark Detection

>> Image Recognition: One-Shot Learning

>> What Is Neural Style Transfer?

>> Image Processing: Graph-based Segmentation

>> Understanding Otsu’s Method for Image Segmentation

>> Introduction to Triplet Loss

>> How Do Siamese Networks Work in Image Recognition?

>> How Do Eigenfaces Work?

>> Image Processing: Sampling and Quantization

>> Computer Vision: Determining the Distance From an Object in a Video

>> Single Shot Detectors (SSDs)

>> Computer Vision: Differences Between Low-Level and High-Level Features

>> What Is Space Carving?

>> VAE Vs. GAN For Image Generation

>> Translation Invariance and Equivariance in Computer Vision

>> Residual Networks

>> Introduction to Optical Flow

>> Fast R-CNN: What is the Purpose of the ROI Layers?

>> An Introduction to Computer Vision

>> How Do Blurs in Images Work?

>> The Viola-Jones Algorithm

>> How Does Pose Estimation Work?

>> Spatial Pyramid Pooling

>> Object Detection: SSD Vs. YOLO

>> Differences Between Computer Vision and Image Processing

>> What Is a Feature Descriptor in Image Processing?

>> How Does Optical Character Recognition Work

>> Computer Vision: Stereo 3D Vision

>> What Are Image Histograms?

>> Computer Vision: Popular Datasets

>> Instance Segmentation vs. Semantic Segmentation

>> How to Handle Large Images to Train CNNs?

>> Object Recognition Tasks and Their Differences

>> What Is “Energy” in Image Processing?

>> How to Use Gabor Filters to Generate Features for Machine Learning

>> The Curse of Dimensionality

>> What Is YOLO Algorithm?

>> Disparity Map in Stereo Vision

>> Algorithm for Handwriting Recognition

>> Intersection Over Union for Object Detection

>> Mean Average Precision in Object Detection

>> The Reparameterization Trick in Variational Autoencoders

>> Applications of Generative Models

>> Calculate the Output Size of a Convolutional Layer

>> Using GANs for Data Augmentation

>> How to Design Deep Convolutional Neural Networks?

>> What Is the Difference Between Labeled and Unlabeled Data?

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