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Convolutional Neural Network
European Journal of Trauma and Emergency Surgery • Vol 49 • No 2
Development and external validation of automated detection, classification, and localization of ankle fractures: inside the black box of a convolutional neural network (CNN)
2022
Article

Convolutional Neural Network

Artificial neural network

Convolutional neural network ( CNN ) is a regularized type of feed- forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels. However, applying cascaded convolution (or cross-correlation) kernels, only 25 neurons are required to process 5x5-sized tiles. Higher-layer features are extracted from wider context windows, compared to lower-layer features.

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European Journal of Trauma and Emergency Surgery • Vol 49 • No 2
Development and external validation of automated detection, classification, and localization of ankle fractures: inside the black box of a convolutional neural network (CNN)
2022
Click Convolutional Neural Network Vs:
Artificial Intelligence
Receiver Operating Characteristic
Ankle
Radiography
Training, Validation, And Test Data Sets
Segmentation Fault
Medicine
Fibula
Computer Science
Click Convolutional Neural Network Vs:
Orthodontics
Machine Learning
Radiology
Tibia
Cartography
Geography
Geotechnical Engineering