Computer Vision

Explore Computer Vision through related topics and the articles other pages reference most.

206 articlesSearch and filter Follow updates by RSS

Explore articles

Browse subtopics: Neural Networks

Articles that also belong to these categories. Counts cover all of Computer Vision.

All articles (206)Deep Learning (53)Machine Learning (41)AI Models (39)Generative AI (37)AI Benchmarks (19)Multimodal AI (18)Neural Networks (17)Chinese AI (16)AI Companies (15)Meta AI (14)Robotics (14)Artificial Intelligence (13)Data & Datasets (13)Image Generation (13)AI Tools & Products (12)Open Source AI (12)Video Generation (11)Autonomous Vehicles (7)World Models (7)Natural Language Processing (6)People (6)AI Research (5)Model Architecture (5)Transformer Models (5)AI Hardware (4)Embodied AI (4)AI Ethics (3)AI Events (3)Developer Tools (3)Google (3)Model Evaluation (3)Training & Optimization (3)AI History (2)Google DeepMind (2)Healthcare AI (2)Interpretability (2)Large Language Models (2)AI Agents (1)AI for Science (1)Algorithms (1)Companies (1)Computer Science (1)Defense AI (1)Enterprise AI (1)Information Retrieval (1)Mathematics (1)Microsoft (1)NVIDIA (1)Physical AI (1)Robotics Companies (1)Statistics (1)

Showing 1-17 of 17 articles

ConvNeXt

ConvNeXt is a family of pure convolutional neural network (CNN) models that match or beat Vision Transformers on standard vision benchmarks

Deep Learning Neural Networks

Convolutional Neural Network

A convolutional neural network (CNN, or ConvNet) is a neural network that uses convolution-like linear operators in at least some layers.

Deep Learning Machine Learning

Convolutional Operation

The convolutional operation is a mathematical procedure that combines two functions to produce a third function expressing how the shape of one is modified by the other.

Machine Learning Neural Networks

DenseNet

DenseNet (Densely Connected Convolutional Networks) is a convolutional neural network architecture that connects every layer to every other layer in a feed-forward fashion

Deep Learning Neural Networks

Depthwise separable convolutional neural network (sepCNN)

A depthwise separable convolutional neural network (often abbreviated sepCNN) is a convolutional neural network that replaces standard convolution layers with depthwise separable convolutions.

Model Architecture Neural Networks

EfficientNet is a family of convolutional neural network architectures and a model-scaling method that uniformly scales network depth, width, and input resolution with a single compound coefficient, developed…

Deep Learning Neural Networks

Inception (deep learning)

Inception is a family of convolutional neural network (CNN) architectures developed by researchers at Google, first introduced in 2014.

Deep Learning Neural Networks

LeNet

LeNet is the pioneering family of convolutional neural networks developed by Yann LeCun and collaborators at AT&T Bell Labs between roughly 1988 and 1998 to read handwritten characters

Artificial Intelligence Deep Learning

MobileNet

MobileNet is a family of efficient convolutional neural network (CNN) architectures developed by Google for mobile and edge AI applications.

AI Hardware Deep Learning

NeRF

Neural Radiance Fields (NeRF) is a method for synthesizing photorealistic novel views of a 3D scene by encoding the scene as a continuous 5D function (3D position plus 2D viewing direction) inside a single…

Deep Learning Neural Networks

Pooling

Pooling is a downsampling operation in neural networks that aggregates each local region of a feature map into a single summary value

Neural Networks

ResNet

ResNet, short for residual network, is a family of deep convolutional neural networks introduced by Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun at CVPR 2016.

Deep Learning Neural Networks

Spatial Pooling

Spatial pooling is a downsampling operation in convolutional neural networks (CNNs) that replaces a local region of a feature map with a single summary statistic, such as the maximum or the average of the…

Machine Learning Neural Networks

Swin Transformer

The Swin Transformer (Shifted Window Transformer) is a hierarchical vision transformer architecture that computes self-attention within local, non-overlapping windows and introduces a shifted window…

Deep Learning Neural Networks

Translational invariance

Translational invariance (also called translation invariance or shift invariance) is the property of a function, system, or machine learning model whose output does not change when its input is translated…

Deep Learning Neural Networks

VGG

VGG (also called VGGNet) is a deep convolutional neural network architecture, introduced in 2014 by Karen Simonyan and Andrew Zisserman of the Visual Geometry Group at the University of Oxford

Deep Learning Neural Networks

YOLO (object detection)

YOLO (You Only Look Once) is a family of object detection models that treat detection as a single regression problem, predicting bounding boxes and class probabilities directly from full images in one forward…

Deep Learning Neural Networks