SegIt: Empowering Sensor Data Labeling with Enhanced Efficiency and Security
| dc.contributor.author | Zhang, Zhen | en |
| dc.contributor.author | Abraham, Samuel | en |
| dc.contributor.author | Lee, Alex | en |
| dc.contributor.author | Li, Yichen | en |
| dc.contributor.author | Morota, Gota | en |
| dc.contributor.author | Ha, Dong | en |
| dc.contributor.author | Shin, Sook | en |
| dc.date.accessioned | 2025-01-09T17:36:08Z | en |
| dc.date.available | 2025-01-09T17:36:08Z | en |
| dc.date.issued | 2024-08-02 | en |
| dc.date.updated | 2025-01-01T08:53:13Z | en |
| dc.description.abstract | SegIt is a novel, user-friendly, and highly efficient sensor data labeling tool designed to tackle critical challenges such as data privacy, synchronization accuracy, and memory efficiency inherent in existing labeling tools. While many current sensor data labeling tools provide free online services, they typically necessitate users to upload unlabeled sensor data, alongside video or audio references, to cloud storage for labeling. Nevertheless, such third-party storage exposes user data to potential security risks. SegIt, an innovative open-source tool, provides a software solution for tagging unlabeled sensor data directly on a local computer, ensuring enhanced accuracy, convenience, and, most importantly, data security. | en |
| dc.description.version | Published version | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | https://doi.org/10.1145/3696271.3696287 | en |
| dc.identifier.uri | https://hdl.handle.net/10919/124010 | en |
| dc.language.iso | en | en |
| dc.publisher | ACM | en |
| dc.rights | Creative Commons Attribution 4.0 International | en |
| dc.rights.holder | The author(s) | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
| dc.title | SegIt: Empowering Sensor Data Labeling with Enhanced Efficiency and Security | en |
| dc.type | Article - Refereed | en |
| dc.type.dcmitype | Text | en |