Machine Learning

LiDAR point cloud data serves as an machine vision alternative other than image. Its advantages when compared to image and video includes depth estimation and distance measruement. Low-density LiDAR point cloud data can be used to achieve navigation, obstacle detection and obstacle avoidance for mobile robots. autonomous vehicle and drones. In this metadata, we scanned over 1200 objects and classified it into 4 groups of object namely, human, cars, motorcyclist.

Silk fibroin is the structural fiber of the silk filament and it is usually separated from the external fibroin by a chemical process called degumming. This process consists in an alkali bath in which the silk cocoons are boiled for a determined time. It is also known that the degumming process impacts the property of the outcoming silk fibroin fibers.

Automatic humor detection has interesting use cases in modern technologies, such as chatbots and virtual assistants. Existing humor detection datasets usually combined formal non-humorous texts and informal jokes with incompatible statistics (text length, words count, etc.). This makes it more likely to detect humor with simple analytical models and without understanding the underlying latent lingual features and structures.

Dataset used in the article "On the shape of timing distributions in free text keystroke dynamics profiles". Contains CSV files with the timing features (hold times and flight times) of every keypress in three free text datasets used in previous studies, by the author (LSIA) and two other unrelated groups (KM from and PROSODY, subdivided in GAY, GUN, and REVIEW). The timing features are grouped by dataset, user, task, virtual key code, and feature. Two different languages are represented, Spanish in LSIA and English in KM and PROSODY.