-
Deep Fault Diagnosis, Explainability and Information Fusion for Rotary Machinery +강의담기
학문/산업 분야별 ▶ 인공지능 ▶
The objective of this talk is to address some challenges and recent results on fault diagnosis of mechanical systems, with a focus on advanced artificial intelligence algorithms developments. Specifically, different deep learning models such as deep supervised, unsupervised and reinforcement learning algorithms are examined to establish a trustworthy intelligence fault diagnosis model. The talk will be concluded with some results on the development of explainable intelligence fault diagnosis framework based on post-hoc visualization methods as well as multi-source information fusion with complementary transferability metric for mechanical fault diagnosis.
강의기간 : 2023-11-01 ~ 2023-11-01 강의수 : 1 최근 업데이트 : 2024-02-19 조회 : 18
-
Stepwise AI Models in Clinical Workflows +강의담기
학문/산업 분야별 ▶ 인공지능 ▶
Artificial intelligence, particularly deep learning, has gained widespread popularity across various medical applications. The current role of AI is to provide support to clinicians, physicians, and patients, ultimately enhancing the performance of a range of tasks such as noise reduction, segmentation, classification, regression, lesion detection, and risk prediction. Sometimes, a complex hierarchical pipeline, or pathway, can be established. This requires breaking down sub-tasks, which can be addressed by a single extensive model or subdivided into smaller, more specialized models. While a single, large model may be convenient (Foundation Model, LLM), it becomes challenging to assess or interpret results for individual sub-tasks, particularly when their performance is suboptimal. As a solution, we can divide these sub-tasks and employ a dedicated small model for each one. To maximize efficiency, closely related sub-tasks can share specific layers within a deep learning model. During this presentation, we will provide a comprehensive overview of the entire pipeline development process, including data cleansing strategies.
강의기간 : 2023-11-15 ~ 2023-11-15 강의수 : 1 최근 업데이트 : 2023-11-20 조회 : 41
-
Reverse-Engineering the Brain: From Brain-Computer Interface to Neuroergonomics and Beyond +강의담기
학문/산업 분야별 ▶ 인공지능 ▶ 세미나 및 튜토리얼
In this talk Dr.
더보기+
Nam will present his recent BCI and neuroergonomics studies conducted to bridge
some of the gaps. After discussing
possibilities and new applications of neural interfacing technology, he will
open the floor for questions from the audience on any aspects of his BCI and
neuroergonomics research.강의기간 : 2022-05-31 ~ 2022-05-31 강의수 : 1 최근 업데이트 : 2022-06-03 조회 : 339
-
Artificial Intelligence and Brain Science +강의담기
학문/산업 분야별 ▶ 인공지능 ▶
Human brain functions have long served as the targets of development of artificial intelligent systems. Findings in neuroscience have provided guidance at multiple levels in the designs of machine learning architectures and algorithms. Today’s neuroscience, in turn, necessitates applications of artificial intelligence and machine learning algorithms for making sense of huge datasets.
In this talk, I review examples of co-evolution of AI and brain science and consider how they can help each other for further progress.
강의기간 : 2017-10-20 ~ 2017-10-20 강의수 : 1 최근 업데이트 : 2017-10-20 조회 : 1591
-
Time-based Localization without synchronization: principles and applications +강의담기
학문/산업 분야별 ▶ 인공지능 ▶ 세미나 및 튜토리얼
강의기간 : 2017-04-04 ~ 2017-04-04 강의수 : 1 최근 업데이트 : 2017-04-10 조회 : 1363
-
A Hybrid Brain-Computer Interface (hBCI) for Behaviorally Non-Responsive Patients +강의담기
학문/산업 분야별 ▶ 인공지능 ▶ 세미나 및 튜토리얼
In this talk Dr. Nam will present his recent project that deal with research and development of a hybrid BCI system to establish communication with behaviorally nonresponsive patients, or patients who are not able to produce any form of consistent behavioral output.
더보기+강의기간 : 2016-05-26 ~ 2016-05-26 강의수 : 1 최근 업데이트 : 2016-05-27 조회 : 2759