22 июн. 2018 г. · This article focuses on the basic concepts of CNN and their application to various radiology tasks, and discusses its challenges and future directions.

This study provides the conceptual understanding of CNN along with its three most common architectures, and learning algorithms.

15 янв. 2023 г. · Convolutional neural networks (CNNs) are deep learning algorithms commonly used in wide applications. CNN is often used for image classification, segmentation, ...

23 мар. 2024 г. · This paper presents an elementary understanding of CNN components and their functions, including input layers, convolution layers, pooling layers, activation ...

31 мар. 2021 г. · This review attempts to provide a more comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field.

22 июн. 2018 г. · This review article offers a perspective on the basic concepts of CNN and its application to various radiological tasks, and discusses its challenges and ...

Convolutional neural network is the most widely used deep learning model in feature learning for large-scale image classification and recognition.

Convolutional neural networks (CNNs) are one of the main types of neural networks used for image recognition and classification.

Convolutional neural networks (CNNs) are deep learning algorithms commonly used in wide applications. CNN is often used for image classification, segmentation, ...

A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization. Feedforward neural net · Computer vision · Filter (signal processing) · LeNet