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Everything about LeNet
Convolutional neural network structure
LeNet is a series of convolutional neural network architectures created by a research group at AT&T Bell Laboratories between 1988 and 1998, centered around Yann LeCun. They were designed for reading small grayscale images of handwritten digits and letters, and were used in ATMs for reading cheques. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: LeNetA 5-minute orientation
- Skim a recent paper: Spatial-spectral classification of hyperspectral remote sensing images using 3D CNN based LeNet-5 architectureInfluential work since 2022
- Pick up a classic book: Memoires de Monsieur l*** Conseiller D'etatThe most-reprinted book on the subject
- Read the landmark paper: Development of a LeNet-5 Gas Identification CNN Structure for Electronic NosesCited 185 times
- Go sideways: MNIST databaseA 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)
Development of a LeNet-5 Gas Identification CNN Structure for Electronic Noses
Sleep apnea detection from a single-lead ECG signal with automatic feature-extraction through a modified LeNet-5 convolutional neural network
Intelligent fault diagnosis of hydraulic piston pump combining improved LeNet-5 and PSO hyperparameter optimization
A Modified LeNet CNN for Breast Cancer Diagnosis in Ultrasound Images
Rolling-Element Bearing Fault Diagnosis Using Improved LeNet-5 Network
An Improved LeNet-Deep Neural Network Model for Alzheimer’s Disease Classification Using Brain Magnetic Resonance Images
A robust system for road sign detection and classification using LeNet architecture based on convolutional neural network
A Lightweight Model for Traffic Sign Classification Based on Enhanced LeNet‐5 Network
🆕 Influential since 2022
Spatial-spectral classification of hyperspectral remote sensing images using 3D CNN based LeNet-5 architecture
Advancements in Cataract Detection: The Systematic Development of LeNet-Convolutional Neural Network Models
A novel deep LeNet-5 convolutional neural network model for image recognition
An enhanced deep learning framework for prostate cancer detection using modified VGG16 and LeNet-MobileNetV2 integration
Enhanced Fault Diagnosis in Rotating Machinery Using a Hybrid CWT-LeNet-5-LSTM Model: Performance Across Various Load Conditions
📚 Books worth reading
- 📕Memoires de Monsieur l*** Conseiller D'etatPierre Lenet · 2018
- 📕Nivreshet le-nets ha-ḥamah be-TsiyonShpiṭtser, Ḥiya Daṿid ben Yosef ha-Leṿi · 1898
Pythonで学ぶディープラーニングの理論と実装 · 2016- 📕Go Play in the Traffic!Lenet Compton · 2014
- 📕How we got the BibleLenet Hadley Read · 1985
- 📕Bordeaux Sous la Fronde, 1650-1653Antoine Saintmarc · 2018
The Lord's holy daysLenet Hadley Read · 2002- 📕My PhilosophyLenet Leski · 1994
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- MNIST database The MNIST database (Modified National Institute of Standards and Technology database) is a large database of handwritten digits that is commonly used for…
- AlexNet AlexNet is a convolutional neural network architecture developed for image classification tasks, notably achieving prominence through its performance in…
- 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…
- 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…
- Yann LeCun Yann André Le Cun (/ləˈkʌn/ lə-KUN; French: [ləkœ̃]; usually spelled LeCun; born 8 July 1960) is a French-American computer scientist working in the fields…
- Time delay neural network Time delay neural network (TDNN) is a multilayer artificial neural network architecture whose purpose is to 1) classify patterns with shift-invariance…
- Léon Bottou Léon-Yves Bottou (French pronunciation: [leɔ̃ bɔtu]; born 1965) is a French computer scientist best known for his work in machine learning and data compression…
- Weight initialization In deep learning, weight initialization or parameter initialization describes the initial step in creating a neural network. A neural network contains…