Machine learning
Samsung Electronics Co. Ltd. has been granted a patent for an Equipment Front End Module (EFEM) and a destructive analysis automation apparatus, according to a patent published by the United States Patent and Trademark Office (USPTO). The patent, filed on April 1, 2022, and published online on July 1, 2025,
Machine learning
Researchers at Hainan University have proposed an innovative approach to image denoising, leveraging deep learning techniques to improve denoising performance. The study, published in the International Journal of Pattern Recognition and Artificial Intelligence, presents an information-enhanced image denoising framework that incorporates both spatial and frequency-domain features. This method, which integrates
Machine learning
Researchers at the University of Louisville have made a groundbreaking discovery in the field of robotics, developing a local explainability mechanism for robotic grasp failure prediction. This mechanism enhances machine learning transparency at the instance level, addressing the critical need for transparent and reliable grasp failure prediction systems. The study,
Machine learning
A new breakthrough in artificial intelligence and machine learning has been achieved by researchers from Manipal Academy of Higher Education, who have successfully integrated digital twins with Wireless Body Area Networks (WBAN) for predictive health monitoring. The study uses machine learning algorithms to process data from WBAN sensors, enabling proactive
Machine learning
Researchers from Hanyang University have developed a novel frequency modulated continuous wave (FMCW) radar-based machine learning system to predict and identify infants at high risk for poor neurodevelopmental outcomes. The system analyzes 3-dimensional (3D) range-angle-time data cube of infant movements using a radar sensor and detects abnormal movements. A new
Machine learning
A new study on machine learning has yielded promising results in detecting driver drowsiness, a leading cause of traffic accidents. Researchers from the American University of the Middle East have proposed a system that uses heart rate variability (HRV) analysis to assess driver drowsiness, leveraging wearable devices equipped with photoplethysmography
Machine learning
Researchers at Tianjin University have developed a new method for detecting and diagnosing faults in district heating systems using machine learning algorithms. The method, known as MASDM-MRM-CNNBiLSTM, integrates machine learning and statistical analysis to accurately predict sensor readings and detect anomalies. According to the study, the proposed method yields an
Machine learning
Researchers from the Cancer Hospital in Beijing, China, have developed a CT-based deep learning radiomics nomogram to predict early recurrence in patients with pancreatic cancer. The model, which integrates feature scores, clinical factors, and imaging data, demonstrated superior classification performance and excellent predictive accuracy in a multicenter study. This breakthrough
Machine learning
Researchers from the All India Institute of Medical Sciences (AIIMS) have been investigating the potential of artificial intelligence (AI) to predict cervical cancer recurrence and survival rates. According to a recent study, AI has emerged as a transformative tool in oncology, providing advanced methodologies for analyzing large-scale medical data and
Machine learning
Researchers at Hamamatsu Photonics K.K. have developed a wafer conveyance unit and method for semiconductor failure analysis apparatus, designed to hold wafers firmly during conveyance without hindering each function of the apparatus. The wafer conveyance unit includes a fixing unit, a conveyance unit, and a ring portion that partitions
Machine learning
A new study by researchers from Veer Kunwar Singh University has explored the potential of artificial intelligence in enhancing e-learning experiences for students in India's educational institutions. The study, which analyzed data from 605 students from various schools across India, focused on the impact of AI-driven social learning
Machine learning
Researchers at the University of California Los Angeles (UCLA) have successfully validated a machine learning algorithm that generates cellularity prediction maps (CPM) from multiparametric MRI data to non-invasively evaluate tumor cellularity in brain cancer patients. The study, published in the Journal of Neuro-Oncology, found that the CPM values accurately predicted
