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Everything about Convolutional neural network
Type of feedforward neural network
A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter optimization. This type of deep learning network has been applied to process and make predictions from many different types of data including text, images and audio. CNNs are the de-facto standard in deep learning-based approaches to computer vision and image processing, and have only recently been replaced—in some cases—by newer architectures such as the transformer. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Convolutional neural networkA 5-minute orientation
- Skim a recent paper: Learning a Single Convolutional Layer Model for Low Light Image EnhancementInfluential work since 2022
- Pick up a classic book: Neural networksThe most-reprinted book on the subject
- Read the landmark paper: Predicting drug–disease associations through layer attention graph convolutional networkCited 409 times
- Go sideways: Convolutional layerA closely related topic
- Go sideways: Types of artificial neural networksA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Predicting drug–disease associations through layer attention graph convolutional network
DO-Conv: Depthwise Over-Parameterized Convolutional Layer
Fabric Defect Detection Using Activation Layer Embedded Convolutional Neural Network
A Five Convolutional Layer Deep Convolutional Neural Network for Plant Leaf Disease Detection
Rotation-Invariant Feature Learning via Convolutional Neural Network With Cyclic Polar Coordinates Convolutional Layer
Cross-Convolutional-Layer Pooling for Image Recognition
Convolutional perfectly matched layer for elastic second-order wave equation
Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning
🆕 Influential since 2022
Learning a Single Convolutional Layer Model for Low Light Image Enhancement
Detection of human activities using multi-layer convolutional neural network
PConv: simple yet effective convolutional layer for generative adversarial network
Convolutional Neural Networks: A Roundup and Benchmark of Their Pooling Layer Variants
Secured Convolutional Layer IP Core in Convolutional Neural Network Using Facial Biometric
đź“š Books worth reading
Neural networksSimon S. Haykin · 1994- 📕Effects of convoluted divergent flap contouring on the performance of a fixed-geometry nonaxisymmetric exhaust nozzleScott C. Asbury · 1999
Fundamentals of Deep LearningNikhil Buduma · 2017
Advances in Neural Networks – ISNN 2013Chengan Guo · 2013
Kkrishnaa's konfessionsSmita Nair Jain · 2008
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
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- Pooling layer In neural networks, a pooling layer is a kind of network layer that downsamples and aggregates information that is dispersed among many vectors into fewer…
- VGGNet The VGGNets are a series of convolutional neural networks (CNNs) developed by the Visual Geometry Group (VGG) at the University of Oxford. The VGG family…
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- Neural network (machine learning) In machine learning, a neural network (NN) or artificial neural network (ANN) is a computational model inspired by the structure and functions of biological…
- DeepDream DeepDream is a computer vision program created by Google engineer Alexander Mordvintsev that uses a convolutional neural network to find and enhance patterns…