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Max Pooling in Convolutional Neural Network

In this video, we will understand what is Max Pooling in Convolutional Neural Network and why do we use it. Max Pooling in Convolutional Neural Network is an important part of the CNN Architecture, ...
Game Rant

All Donkey Kong Bananza Layers and Collectibles

Tom Bowen is a senior editor who loves adventure games and RPGs. He's been playing video games for several decades now and writing about them professionally since 2020. Although he dabbles in news and ...
Frontiers

Automated classification of midpalatal suture maturation using 2D convolutional neural networks on CBCT scans

School of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada Introduction: Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, ...
Frontiers

Optimizing quantum convolutional neural network architectures for arbitrary data dimension

Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This approach is ...
Scientific Research Publishing

Zafar, A., Saba, N., Arshad, A., Alabrah, A., Riaz, S., Suleman, M., et al. (2024) Convolutional Neural Networks: A Comprehensive Evaluation and Benchmarking of Pooling Layer ...

ABSTRACT: Pneumonia remains a significant cause of morbidity and mortality worldwide, particularly in vulnerable populations such as children and the elderly. Early detection through chest X-ray ...
IEEE

Lotus Disease Diagnosis Using Combined CNN and SVM with Max Pooling and Convolutional Layers

Abstract: This study presents an evaluation of a classification model employing convolutional neural network (CNN) and support vector machine (SVM) algorithms for the identification of various ...
IEEE

The treasure beneath convolutional layers: Cross-convolutional-layer pooling for image classification

Abstract: A number of recent studies have shown that a Deep Convolutional Neural Network (DCNN) pretrained on a large dataset can be adopted as a universal image descriptor, and that doing so leads to ...