Optical remote sensing images, with their high spatial resolution and wide coverage, have emerged as invaluable tools for landslide analysis. Visual interpretation and manual delimitation of landslide areas in optical remote sensing images by human is labor intensive and inefficient. Automatic delimitation of landslide areas empowered by deep learning methods has drawn tremendous attention in recent years. Mask R-CNN and U-Net are the two most popular deep learning frameworks for image segmentation in computer vision.

Since the aircraft trajectory data in the field of air traffic management typically lacks labels, it limits the community's ability to explore classification models. Consequently, evaluations of clustering models often focus on the correctness of cluster assignment rather than merely the closeness within the cluster. To address this, we labeled the dataset for both classification and clustering tasks by referring to aeronautical publications. The process of obtaining the ATFM trajectory dataset consists of data sourcing, preprocessing, and annotation.

We used the broad group of 47,692 tweets from the Cyberbullying Classification dataset. This worldwide sourced dataset offers a broad range of examples of cyberbullying, guaranteeing a thorough viewpoint. Our thorough translation and modification procedure guaranteed the dataset's contextual and cultural relevance for the Tamil-speaking population, even though it is not solely from South Asia. These tweets were carefully divided into six classes, each of which represented a different facet of cyberbullying, as well as cases that weren't considered cyberbullying.

This dataset originates from a longitudinal study examining the factors contributing to the progression of cardiovascular disease. P This particular research employs the unprocessed sequential actigraph recordings collected from an actigraph device. We evaluate sleep quality based on the two indicators as proposed in our previous study [3] which are weekly sleep quality ‘SleepQualWeek’, and sleep consistency ‘SleepCons’. SleepQualWeek and SleepCons are calculated using the pre-processed attribute set derived from the MESA dataset.