White blood cell (WBC) classification is a crucial step in assessing a patient's health and validating medical treatment in the medical domain. Hence, efficient computer vision solutions to the classification of WBC will be an effective aid to medica...
This study explores the application of machine learning algorithms in predicting high-risk pregnancy among expectant mothers, aiming to construct an efficient predictive model to improve maternal health management. The study is based on the maternal ...
This paper describes the automatic identification of ivory using Raman spectroscopy data and deep neural network (DNN) models pre-trained on open-source data from inorganic minerals. The proposed approach uses transfer learning (TL) from foundation m...
Driver fatigue is one of the major causes of traffic accidents, particularly for drivers of large vehicles, who are more susceptible to fatigue due to prolonged driving hours and monotonous conditions during their journeys. Existing vision-based driv...
In this study, we developed a digital twin for SARS-CoV-2 by integrating diverse data and metadata with multiple data types and processing strategies, including machine learning, natural language processing, protein structural modeling, and protein s...
The rapid increase in Unmanned Aerial Vehicle (UAV) deployments has led to growing concerns about their detection and differentiation from birds, particularly in sensitive areas like airports. Existing detection systems often struggle to distinguish ...
It is an urgent need to understand the ability of current artificial intelligence (AI) models in simulating atmospheric mesoscale aspects. This paper compares mesoscale kinetic energy spectra from an 11-day experiment simulated by a novel AI-based mo...
Aiming at the student-centered online music learning platform, this study proposes a Course Recommendation Model for Student Learning Interest Evolution (CRM-SLIE) to improve the accuracy and adaptability of the platform's course recommendation. This...
Identifying protein-protein interactions (PPIs) is a foundational task in biomedical natural language processing. While specialized models have been developed, the potential of general-domain large language models (LLMs) in PPI extraction, particular...
Pesticides and other synthetic agrochemicals play a critical role in emerging agricultural practices by enhancing crop productivity and protecting against pests and diseases. However, their widespread application has raised significant concerns about...