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

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

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 ...

Develop an AI-based image classification system using CNN and transfer learning. The project includes data preprocessing, model training, fine-tuning, evaluation with precision, recall, and F1-score, ...

Computer vision model for detecting whether workers are wearing safety helmets in images. Useful for automated safety monitoring in industrial environments.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...

Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, particularly for planning treatment strategies in patients with maxillary transverse deficiency (MTD). Although ...

Artificial neural networks are machine learning models that have been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. These ...

Abstract: This paper investigates the application of Convolutional Neural Networks (CNNs) in MNIST handwritten digit recognition, with a particular focus on optimizing the ResNet-18 model. By ...