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Everything about VGGNet
Series of convolutional neural networks for image classification
The VGGNets are a series of convolutional neural networks (CNNs) developed by the Visual Geometry Group (VGG) at the University of Oxford. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: VGGNetA 5-minute orientation
- Skim a recent paper: Encoding Time Series as Images: A Robust and Transferable Framework for Power System DIM Identification Combining Rules and VGGNetInfluential work since 2022
- Read the landmark paper: Brain Tumor Detection and Multi-Grade Segmentation Through Hybrid Caps-VGGNet ModelCited 144 times
- Go sideways: Neural style transferA closely related topic
- Go sideways: AlexNetA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Brain Tumor Detection and Multi-Grade Segmentation Through Hybrid Caps-VGGNet Model
Deep convolutional neural networks for construction and demolition waste classification: VGGNet structures, cyclical learning rate, and knowledge transfer
Towards Brain Big Data Classification: Epileptic EEG Identification With a Lightweight VGGNet on Global MIC
Multi-level residual network VGGNet for fish species classification
One-dimensional VGGNet for high-dimensional data
Modality Specific CBAM-VGGNet Model for the Classification of Breast Histopathology Images via Transfer Learning
CustomBottleneck-VGGNet: Advanced tomato leaf disease identification for sustainable agriculture
Electrocardiogram signal classification using VGGNet: a neural network based classification model
🆕 Influential since 2022
Encoding Time Series as Images: A Robust and Transferable Framework for Power System DIM Identification Combining Rules and VGGNet
A Study on Pavement Classification and Recognition Based on VGGNet-16 Transfer Learning
Effect of transfer learning on the performance of VGGNet-16 and ResNet-50 for the classification of organic and residual waste
Leaf Disease Classification in Bell Pepper Plant using VGGNet
SVMVGGNet-16: A Novel Machine and Deep Learning Based Approaches for Lung Cancer Detection using Combined SVM and VGGNet-16
📚 Books worth reading
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🔗 Related topics
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- Residual neural network A residual neural network (also referred to as a residual network or ResNet) is a deep learning architecture in which the layers learn residual functions…
- 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…
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- Capsule neural network A capsule neural network (CapsNet) is a machine learning system that is a type of artificial neural network (ANN) that can be used to better model hierarchical…
- 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…