Overview Clear prompts help machine learning models become more accurate and reliable.Role-specific prompts generate focused and practical technical answers.Det ...

This article rounds up some of the most valuable free data science courses offered by top institutions like Harvard, IBM, and ...

When deploying large-scale deep learning applications, C++ may be a better choice than Python to meet application demands or to optimize model performance. Therefore, I specifically document my recent ...

Attempts to censor AI image generators by erasing banned content (such as porn, violence, or copyrighted styles) from the trained models are falling short: a new study finds that current concept ...

This study published in Robot Learning has been focused on water analysis using the combination of decision making and machine learning for a recently developed robotic system. The unique procedure ...

Background Indigenous Mayan-Yucatecan communities in Mexico have a high prevalence of chronic non-communicable diseases (NCDs) such as diabetes, hypertension, obesity and rheumatic diseases (RMDs).

Several significant research studies related to Preventing Phishing Attacks for Cyber Threat Mitigation have been reviewed ...

This project explores landmark image classification using two distinct deep learning approaches in PyTorch. It covers the full lifecycle from data preparation and model training (custom CNN and ...

Aiming at the problems of low classification accuracy and efficiency in traditional image classification methods, an image classification method based on depthwise separation convolution combined mask ...

The classification branch is based on traditional image classification methods. Still, it improves the cross-entropy loss to develop a dynamic adaptive loss, enabling the model to learn ...

Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy. However, most current hyperspectral ...