Deep Learning Cyber-Infrastructure for the Exploration of High Dimensional Multimodal Data

<p dir="ltr">The BisQue Deep Learning (BDL) cyberinfrastructure (CI) project is designed to advance scientific research in fields such as materials science, remote sensing, and bioimaging. By integrating state-of-the-art deep learning and computer vision techniques, BDL-CI provides a...

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Main Author: Connor Levenson (17108584) (author)
Other Authors: BS Manjunath (21789828) (author), Chandrakanth Gudavalli (21789831) (author), Amil Khan (21789836) (author), Charvi Mendiratta (21789838) (author), Bowen Zhang (21789841) (author)
Published: 2025
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Summary:<p dir="ltr">The BisQue Deep Learning (BDL) cyberinfrastructure (CI) project is designed to advance scientific research in fields such as materials science, remote sensing, and bioimaging. By integrating state-of-the-art deep learning and computer vision techniques, BDL-CI provides a scalable, user-friendly platform for managing and analyzing large, complex datasets. It addresses key challenges in data curation, domain-specific analysis, and scalable processing of high-dimensional data. The infrastructure supports continuous learning and model updates for tasks including detection, segmentation, localization, classification, and tracking—all backed by a robust database that ensures data integrity and provenance. Built for scalability and efficiency, BDL-CI enables dynamic resource allocation, workflow orchestration, and high-throughput data handling. BisQue service is accessible via the web at UCSB, with source code and documentation available on GitHub</p><p><br></p>