For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it ...
1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
AI models still lose track of who is who and what's happening in a movie. A new system orchestrates face recognition and staged summarization, keeping characters straight, and plots coherent across ...
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4 reasons to learn Python (even if you don't want to be a developer)
It's time to join the Pythonistas.
Abstract: The phenomenon of cyberbullying has emerged as a critical challenge in the digital landscape which poses detrimental effects on individuals and broader societal frameworks. A viable approach ...
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 ...
Objective: This review aimed to evaluate the predictive performance of text-based depression models that used standard labels, and to identify text resources, text representation, model architecture, ...
Background Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial ...
Additionally, the effects of social media platform type, machine learning approach, and use of outcome measures in depression prediction models need attention. Analyzing social media texts for ...
Two complementary approaches were employed: Study 1 analyzed 1,902 Weibo posts containing “diet” and “social” keywords through latent Dirichlet allocation topic modeling and semantic network analysis ...
Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...
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