General Analysis
General analysis encompasses a broad range of methodologies applied across diverse scientific domains to extract meaningful insights from data. Current research focuses on developing robust and efficient analytical techniques, including the application of machine learning models like convolutional neural networks, graph neural networks, and transformer architectures, as well as statistical methods for data modeling and hypothesis testing. These advancements are improving the accuracy and efficiency of analyses in fields ranging from medical image processing and materials science to social media analysis and autonomous systems, ultimately leading to more reliable scientific findings and improved decision-making in various applications.
Papers
Analysis and Comparison of Classification Metrics
Luciana Ferrer
VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models
Felix Vogel, Nina Shvetsova, Leonid Karlinsky, Hilde Kuehne
mmBody Benchmark: 3D Body Reconstruction Dataset and Analysis for Millimeter Wave Radar
Anjun Chen, Xiangyu Wang, Shaohao Zhu, Yanxu Li, Jiming Chen, Qi Ye
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis
Yan Zhao, Liwei Deng, Xuanhao Chen, Chenjuan Guo, Bin Yang, Tung Kieu, Feiteng Huang, Torben Bach Pedersen, Kai Zheng, Christian S. Jensen
An Analysis of the Differences Among Regional Varieties of Chinese in Malay Archipelago
Nankai Lin, Sihui Fu, Hongyan Wu, Shengyi Jiang