CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...

Abstract: A lightweight Convolutional Neural Network (CNN) has become one of the major studies in machine learning field to optimize its potential for employing it on the resource-constrained devices.

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.

1 School of Electronics and Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou, China 2 Department of Mechanical and Electrical Engineering, Henan Vocational College of ...

• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).

Councilman Lee Vogler suffered from extreme burns. The man who allegedly set fire to a Virginia councilman in an apparent personal attack has admitted to the crime, according to court documents.

Our ability to understand the nervous system has been hindered by the difficulty of constructing good predictive models of neurons and circuits. This difficulty persists despite vast accumulated ...