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Found 6 papers, 1 papers with code
Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot
For instance, developers can ask for new code directly from within their IDEs by writing natural language prompts, and integrated services based on generative AI, such as Copilot, immediately respond to prompts by providing ready-to-use code snippets.
Unsupervised Deep Learning-based clustering for Human Activity Recognition
A large amount of data would be available due to the wide spread of mobile devices equipped with inertial sensors that can collect data to recognize human activities.
Homogenization of Existing Inertial-Based Datasets to Support Human Activity Recognition
The final aim of our work is the definition and implementation of a platform that integrates datasets of inertial signals in order to make available to the scientific community large datasets of homogeneous signals, enriched, when possible, with context information (e. g., characteristics of the subjects and device position).
FILO: FIx-LOcus Localization for Backward Incompatibilities Caused by Android Framework Upgrades
Mobile operating systems evolve quickly, frequently updating the APIs that app developers use to build their apps.
Software Engineering
Personalization in Human Activity Recognition
In the recent years there has been a growing interest in techniques able to automatically recognize activities performed by people.
UniMiB SHAR: a new dataset for human activity recognition using acceleration data from smartphones
Nowadays, publicly available data sets are few, often contain samples from subjects with too similar characteristics, and very often lack of specific information so that is not possible to select subsets of samples according to specific criteria.
