Machine learning
Research at Xi'an Jiaotong University has successfully demonstrated the use of artificial intelligence (AI) in identifying bacterial infections in decomposed tissue under varying temperature conditions. The study utilized pathology images and AI algorithms to classify bacterial infections, showing strong classification efficacy across all tested temperatures. The findings have
Machine learning
Researchers from the Chaitanya Bharathi Institute of Technology have made a significant breakthrough in the field of machine learning by designing and optimizing a MIMO dielectric resonator antenna with high gain and circular polarization features. Using machine learning algorithms, such as Decision Tree and Random Forest, the team was able
Machine learning
Artificial intelligence has transformed many general knowledge areas, such as computer vision and language processing, but has yet to be widely applied in expert knowledge areas like healthcare due to data scarcity and high annotation costs. Researchers at the Chinese Academy of Sciences have pioneered a new approach called Human-in-the-Loop
Machine learning
According to research from the Indian Institute of Technology Roorkee, groundwater contamination is a pressing issue in the Ambagarh Chowki region of Chhattisgarh, India, posing significant health risks to the local population. The study analyzed 52 villages and found that 48% of the samples had water quality suitable for drinking
Machine learning
Researchers from the Indian Council of Agricultural Research (ICAR) Central Island Agricultural Research Institute have developed artificial neural network (ANN) models to estimate soil moisture in Indian tropical islands. The study used Sentinel-1A C-band synthetic aperture radar (SAR) data and other auxiliary data from Sentinel-2A and Landsat 8 to analyze
Machine learning
Researchers at the National University of Defense Technology in Changsha, People's Republic of China, have made significant breakthroughs in fluid mechanics research using neural network technology. The study, led by Chenglong Wang, utilized high-performance computing and advanced experimental methods to develop a new paradigm in fluid mechanics research.
Machine learning
Researchers at Linkoping University have made a significant advancement in artificial intelligence by developing a new generative model called TransFusion. This model is capable of generating high-quality long-sequenced time-series data, surpassing the previous limit of 384 sequences. The research, published in Machine Learning with Applications, aims to address the limitations
Machine learning
The increasing presence of artificial intelligence (AI) in our daily lives raises important questions about data privacy. AI tools and technologies can make life easier, but they often collect large amounts of data, sometimes without people even realizing their data is being collected. This information can be used to identify
Machine learning
Researchers from Hubei University of Arts & Science have conducted new research on machine learning, with a focus on the state of health estimation of lithium-ion batteries. According to the study, the battery data from the existing publicly available dataset was measured under uninterrupted charge/discharge experiments. However, the aging
Machine learning
Researchers from the Islamic Azad University and University of Zanjan have made significant advancements in using Machine Learning (ML) and Deep Learning (DL) algorithms to improve computational efficiency in predicting the parameters of a 2D permanent magnetic lattice. By applying these algorithms, the team was able to achieve high accuracy
Machine learning
Researchers at Zhejiang University of Technology in Hangzhou, People's Republic of China, have made significant advancements in liver lesion detection using a novel weakly-supervised learning framework. This innovative approach leverages generative adversarial networks to translate abnormal data into normal data, enabling the detection of lesions without requiring pixel-
Machine learning
Linear Programs (LPs) are one of the major building blocks of AI and have made significant strides in differentiable optimizers for learning systems, according to new research. The study, conducted by researchers at the Technical University of Darmstadt, aimed to address the non-explainability of LPs, which are often considered white-box
