Abstract: Recent advancements in deep neural networks heavily rely on large-scale labeled datasets. However, acquiring annotations for large datasets can be challenging due to annotation constraints.

Being invited to present research at an international academic conference is an honor for any seasoned professional. But for ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Google launched four official and confirmed algorithmic updates in 2025, three core updates and one spam update. This is in comparison to last year, in 2024, where we had seven confirmed updates, then ...

This meta-analysis included articles that reported the diagnostic performance of deep learning algorithms based on dermatoscopy for detecting BCC. The quality and risk of bias in the included studies ...

Welcome to the Data Structures and Algorithms Repository! My aim for this project is to serve as a comprehensive collection of problems and solutions implemented in Python, aimed at mastering ...

Abstract: Current traditional learning path planning methods are difficult to meet the needs of personalized learning, especially in immersive learning environments, where learners face problems such ...

Created this repository. 🔜 Working on Stage 1: Python & NumPy Refresh. First output: Data exploration with Pandas/Matplotlib. 🔜 Next: Implement Linear Regression with NumPy.

Deep learning-based prediction models outperformed traditional machine learning models, namely logistic regression, decision tree, naive Bayes, random forest, and support vector machine, on all the ...