Classification, as a research area, primarily refers to methods and theory for assigning objects, instances, or signals to discrete categories based on observed features, typically within statistics, machine learning, and pattern recognition. It encompasses the study of supervised learning algorithms (e.g., logistic regression, support vector machines, decision trees, neural networks), loss functions, generalization error, and evaluation metrics such as accuracy, precision, recall, and ROC analysis. Research focuses on consistency, sample complexity, robustness, feature representation, handling class imbalance, and extensions such as multilabel, hierarchical, probabilistic, and open-set classification, often with applications across biology, medicine, engineering, and information retrieval.
A database, collecting and classifying tile-like patterns in biology, aims to be a resource and research catalyst. The human eye is drawn to the rhythmic beauty of tiled patterns, which occur abundantly in nature.
Molecular & Computational biology
Nov 11, 2025
0
19
How can artificial intelligence (AI) help astronomers identify celestial objects in the night sky? This is what a recent study published in Nature Astronomy hopes to address as an international team of researchers investigated ...
Astronomy
Oct 27, 2025
0
33
In research that could improve weather forecasting and winter driving safety, a University of Michigan-led study distinguished nine distinct precipitation types—varieties of rain, snow and mixed-phase (e.g., sleet)—using ...
Environment
Oct 7, 2025
0
33
A new AI-powered tool has reduced astronomers' workload by 85%—filtering through thousands of data alerts to identify the few genuine signals caused by supernovae (powerful explosions from dying stars). The findings are published ...
Astronomy
Sep 9, 2025
0
56
How can artificial intelligence (AI) be used to locate lunar pits and skylights, which are surface depressions and openings, respectively, that serve as entrances to lava caves and lava tubes? This is what a recent study ...
Planetary Sciences
Jul 30, 2025
0
103
A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according to a paper recently published ...
Astronomy
Jul 25, 2025
0
61
Researchers at the University of Osaka have developed a deep learning model for rapid building damage assessment after floods using satellite imagery. This research establishes the first systematic benchmark for this task ...
Environment
Jul 24, 2025
0
27
Using a high-throughput fluorescence microscopy system and machine learning algorithms, oxidative stress-related changes in protein localization have been mapped by researchers from Japan. Furthermore, a comprehensive database ...
Cell & Microbiology
Jul 11, 2025
0
17
Through his research at Caltech, a local high school student revealed 1.5 million previously unknown objects in space, broadened the potential of a NASA mission, and published a single-author paper.
Astronomy
Apr 11, 2025
2
1310
A research team led by Prof. Gao Xiaoming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has improved residual neural networks to accurately classify and identify microplastics using low-quality ...
Environment
Mar 14, 2025
0
39
