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Everything about AlexNet
Influential 2012 deep convolutional neural network
AlexNet is a convolutional neural network architecture developed for image classification tasks, notably achieving prominence through its performance in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). It classifies images into 1,000 distinct object categories and is regarded as the first widely recognized application of deep convolutional networks in large-scale visual recognition. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: AlexNetA 5-minute orientation
- Skim a recent paper: Corona Detection and Power Equipment Classification Based on GoogleNet-AlexNet: An Accurate and Intelligent Defect Detection Model Based on Deep Learning for Power Distribution LinesInfluential work since 2022
- Pick up a classic book: Pythonで学ぶディープラーニングの理論と実装The most-reprinted book on the subject
- Read the landmark paper: InceptionTime: Finding AlexNet for time series classificationCited 1,777 times
- Go sideways: Alex KrizhevskyA closely related topic
- Go sideways: Convolutional layerA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
InceptionTime: Finding AlexNet for time series classification
Modified Alexnet architecture for classification of diabetic retinopathy images
Pathological brain detection based on AlexNet and transfer learning
Pre-Trained AlexNet Architecture with Pyramid Pooling and Supervision for High Spatial Resolution Remote Sensing Image Scene Classification
AlexNet Convolutional Neural Network for Disease Detection and Classification of Tomato Leaf
Detection of abnormal brain in MRI via improved AlexNet and ELM optimized by chaotic bat algorithm
On the Performance of GoogLeNet and AlexNet Applied to Sketches
Maize Leaf Disease Identification Based on Feature Enhancement and DMS-Robust Alexnet
🆕 Influential since 2022
Corona Detection and Power Equipment Classification Based on GoogleNet-AlexNet: An Accurate and Intelligent Defect Detection Model Based on Deep Learning for Power Distribution Lines
An Effective and Novel Approach for Brain Tumor Classification Using AlexNet CNN Feature Extractor and Multiple Eminent Machine Learning Classifiers in MRIs
Efficient 3D AlexNet Architecture for Object Recognition Using Syntactic Patterns from Medical Images
AlexNet, AdaBoost and Artificial Bee Colony Based Hybrid Model for Electricity Theft Detection in Smart Grids
Accessing Artificial Intelligence for Fetus Health Status Using Hybrid Deep Learning Algorithm (AlexNet-SVM) on Cardiotocographic Data
📚 Books worth reading
Pythonで学ぶディープラーニングの理論と実装 · 2016
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Alex Krizhevsky Alex Krizhevsky is a Canadian computer scientist most noted for his work on artificial neural networks and deep learning. In 2012, Krizhevsky, Ilya Sutskever…
- Convolutional layer In artificial neural networks, a convolutional layer is a type of network layer that applies a convolution operation to the input. Convolutional layers…
- Convolutional neural network A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep…
- 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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- History of artificial neural networks Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. While the computational implementations of ANNs…
- Deep learning In machine learning, deep learning (DL) focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representatio…