… on the global hydrologic cycle and energy balance through thermal forcing. Based on daily
… Large scale atmospheric circulation changes derived from NCEP/NCAR reanalysis reveals …

… Effective execution in this context requires a delicate balance … access and utilize large-scale
datasets, thereby enhancing … for exploratory data analysis, anomaly detection, and creating …

… learning, and handling imbalanced datasets. These algorithms can … Anomaly detection
algorithms identify rare or abnormal … is computationally efficient and suitable for large-scale …

… of abnormal behavior detection for large-scale video data, … the problem of the imbalance
between the foreground target … adversarial network based anomaly detection algorithm, the …

… [Objective] This paper uses semantic auto-encoder to examine the correlation between low-…
[Results] We examined our method with three open datasets of WIKI, MIRFLICKR and NUS-…

… and detection methods were the key issues in fighting product review spam. The acquisition
of large-scale … [Limitations] We did not examine the detection and classification methods for …

… ,this paper provides a large-scale human body complex behavior database DMV action3D
based on … There are 31 different behavioral classes in the database,including daily behaviors,…

… The dependency on large-scale labeled datasets for training deep learning models
remains a constraint, as acquiring diverse and representative fingerprint images can be time-…

… of AER, AND, and Acoustic Anomaly Detection (AAD) algorithms for … using a large scale of
audio datasets are exploited, and the networks are evaluated in different benchmark datasets. …

… defect detection and introduces common data sets for … vector machine for high accuracy
anomaly detection. In: Proceedings of the … Deep learning-based crack damage detection using …