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Artificial Intelligence for Colonoscopy: Past, Present, and Future
Article summarizing the past and present development of colonoscopy video analysis methods, focusing on two categories of artificial intelligence (AI) technologies used in clinical trials, (1) analysis and feedback for improving colonoscopy quality and (2) detection of abnormalities.
Date:
August 2021
Creator:
Tavanapong, Wallapak; Oh, JungHwan; Riegler, Michael; Khaleel, Mohammed I.; Mitta, Bhuvan & de Groen, Piet C.
System:
The UNT Digital Library
A smartphone-based online system for fall detection with alert notifications and contextual information of real-life falls
This article presents the results of a prospective study investigating a proof-of-concept, smartphone-based, online system for fall detection and notification. Apart from functioning as a practical fall monitoring instrument, this system may serve as a valuable research tool, enable future studies to scale their ability to capture fall-related data, and help researchers and clinicians to investigate real-falls.
Date:
August 10, 2021
Creator:
Harari, Yaar; Shawen, Nicholas; Mummidisetty, Chaithanya K.; Albert, Mark & Kording, Konrad P.
System:
The UNT Digital Library
A Gaze into the Internal Logic of Graph Neural Networks, with Logic
Article exploring graph node property prediction. Originally presented as part of the application track at the 38th International Conference on Logic Programming in Haifa, Israel.
Date:
August 4, 2022
Creator:
Tarau, Paul
System:
The UNT Digital Library
A Parallel Convolution and Decision Fusion-Based Flower Classification Method
This article proposes a novel flower classification method that combines enhanced VGG16 (E-VGG16) with decision fusion.
Date:
August 4, 2022
Creator:
Jia, Lianyin; Zhai, Hongsong; Yuan, Xiaohui; Jiang, Ying & Ding, Jiaman
System:
The UNT Digital Library
FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs
Article describes how today's large-scale scientific applications running on high-performance computing (HPC) systems generate vast data volumes. Thus, data compression is becoming a critical technique to mitigate the storage burden and data-movement cost. In this paper, the authors develop a fast and high- ratio error-bounded lossy compressor on GPUs for scientific data (called FZ-GPU).
Date:
August 7, 2023
Creator:
Zhang, Bouyan; Tian, Jiannan; Di, Sheng; Yu, Xiaodong; Feng, Yunhe; Liang, Xin et al.
System:
The UNT Digital Library