日期

2323/07/25

標題

【公告】

內容

以下是為了能夠滿足段落所需的長度而定義的無意義內文,請自行參酌編排。

連結

最新消息

日期

標題

內容

2023/07/25

【Call for papers】

以下是為了能夠滿足段落所需的長度而定義的無意義內文,請自行參酌編排。

2023/07/25

【Call for papers】

以下是為了能夠滿足段落所需的長度而定義的無意義內文,請自行參酌編排。

2023/07/25

【Call for papers】

以下是為了能夠滿足段落所需的長度而定義的無意義內文,請自行參酌編排。

TAAI 2023

The 28th International Conference on Technologies and Applications of Artificial Intelligence (TAAI) series of conferences is an annual leading conference on artificial intelligence and a well-established conference series in Taiwan's AI community. TAAI 2023 is mainly sponsored by the Taiwanese Association for Artificial Intelligence (TAAI) and hosted by the National Yunlin University of Science and Technology (YunTech), Taiwan. The conference will provide a forum for researchers to share their insights in various aspects of artificial intelligence from theory, techniques, applications, and implementation.

以下是為了能夠滿足段落所需的長度而定義的無意義內文,請自行參酌編排。

以下是為了能夠滿足段落所需的長度而定義的無意義內文,請自行參酌編排。

Latest News

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

Latest News

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

Latest News

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

【Annoucement】

Online Paper Submission Link for TAAI 2023 is released.

Aug. 25, 2023

Latest News

2023/07/25

Online Paper Submission Link for TAAI 2023 is released.

2023/07/17

Call for Special Session are released. Check it now!

2023/07/14

Official website is open.

Session Title : Machine Learning for EDA
Session Organizer : Prof. Dun-Wei Cheng
Instituion : National Yunlin University of Science and Technology
E-mail : dunwei@yuntech.edu.tw

We are organizing a special session on " Machine Learning for EDA " for TAAI2023, held in National Yunlin University of Science and Technology, Yunlin County, in Taiwan on December 1-2, 2023.
In recent years, the development of semiconductor technology has led to exponential growth in the scale of integrated circuits (ICs), challenging the scalability and reliability of the circuit design process. To deal with extremely large search spaces with low latency, Electronic Design Automation (EDA) software needs to be more effective and efficient. Machine learning (ML) models have been extensively used to automate the design of digital circuits, replacing pure optimization algorithms. This has significantly reduced the time complexity associated with designing a robust digital IC.
The use of ML for EDA has become a trending topic, with numerous studies proposing the use of ML to improve EDA methods. These studies cover almost all stages of the chip design process, including design space reduction and exploration, logic synthesis, placement, routing, testing, verification, manufacturing, etc. The special session on Machine Learning for EDA aims to apply ML techniques to accelerate EDA tasks. ML methods show great potential in generating high-quality solutions

Session Title : Deep Learning for Various Sources in Smart Applications
Session Organizer : Prof. Rung-Ching Chen and Prof. Alex Long-Sheng Chen
Instituion : Chaoyang University of Technology
E-mail : crching@cyut.edu.tw , lschen@cyut.edu.tw

We are organizing a special session on "Deep Learning for Various Sources in Smart Applications, DLVSMA, for TAAI2023, held in National Yunlin University of Science and Technology, Yunlin County, in Taiwan on December 1-2, 2023. Deep Learning combines high-performance computing leading to unusual solutions for multi-model data analysis problems. Deep Learning-empowered systems can nowadays achieve performance levels in various data analysis tasks comparable to, or even exceeding, those of human beings. These advancements have the potential to open new high-impact applications in different environments. In this special issue, the authors will fully exploit Deep Learning solutions in smart applications through theoretical, methodological, and experimental contributions.

Session Title : AI in Medical Applications (AIMA)
Session Organizer : Prof. Yu-Min Chiang / Prof. Yih-Lon Lin
Instituion : National Formosa University / National Yunlin University of Science and Technology
E-mail : ymchiang@nfu.edu.tw / yihlon@yuntech.edu.tw

We are organizing a special session on "AI in Medical Applications" for TAAI2023, held in National Yunlin University of Science and Technology, Yunlin County, in Taiwan on December 1-2, 2023. AI plays a crucial role in Medical Applications, encompassing various domains, including medical healthcare information systems, medical image processing, medical signal processing, medical education, and medical applications. As AI continues to revolutionize the medical industry, this special session aims to highlight cutting-edge research and advancements in the integration of AI technologies within medical practices.

Session Organizer :

Prof. Dun-Wei Cheng

Institution :

National Yunlin University of Science and Technology

E-mail :

dunwei@yuntech.edu.tw

We are organizing a special session on " Machine Learning for EDA " for TAAI2023, held in National Yunlin University of Science and Technology, Yunlin County, in Taiwan on December 1-2, 2023.
In recent years, the development of semiconductor technology has led to exponential growth in the scale of integrated circuits (ICs), challenging the scalability and reliability of the circuit design process. To deal with extremely large search spaces with low latency, Electronic Design Automation (EDA) software needs to be more effective and efficient. Machine learning (ML) models have been extensively used to automate the design of digital circuits, replacing pure optimization algorithms. This has significantly reduced the time complexity associated with designing a robust digital IC.
The use of ML for EDA has become a trending topic, with numerous studies proposing the use of ML to improve EDA methods. These studies cover almost all stages of the chip design process, including design space reduction and exploration, logic synthesis, placement, routing, testing, verification, manufacturing, etc. The special session on Machine Learning for EDA aims to apply ML techniques to accelerate EDA tasks. ML methods show great potential in generating high-quality solutions

Session Organizer :

Prof. Rung-Ching Chen and Prof. Alex Long-Sheng Chen

Instituion :

Chaoyang University of Technology

E-mail :

crching@cyut.edu.tw , lschen@cyut.edu.tw

We are organizing a special session on "Deep Learning for Various Sources in Smart Applications, DLVSMA, for TAAI2023, held in National Yunlin University of Science and Technology, Yunlin County, in Taiwan on December 1-2, 2023. Deep Learning combines high-performance computing leading to unusual solutions for multi-model data analysis problems. Deep Learning-empowered systems can nowadays achieve performance levels in various data analysis tasks comparable to, or even exceeding, those of human beings. These advancements have the potential to open new high-impact applications in different environments. In this special issue, the authors will fully exploit Deep Learning solutions in smart applications through theoretical, methodological, and experimental contributions.

Session Organizer :

Prof. Yu-Min Chiang / Prof. Yih-Lon Lin

Instituion :

National Formosa University / National Yunlin University of Science and Technology

E-mail :

ymchiang@nfu.edu.tw / yihlon@yuntech.edu.tw

We are organizing a special session on "AI in Medical Applications" for TAAI2023, held in National Yunlin University of Science and Technology, Yunlin County, in Taiwan on December 1-2, 2023. AI plays a crucial role in Medical Applications, encompassing various domains, including medical healthcare information systems, medical image processing, medical signal processing, medical education, and medical applications. As AI continues to revolutionize the medical industry, this special session aims to highlight cutting-edge research and advancements in the integration of AI technologies within medical practices.

Session Organizer :

Prof. Dun-Wei Cheng

Instituion :

National Yunlin University of Science and Technology

E-mail :

dunwei@yuntech.edu.tw

The use of ML for EDA has become a trending topic, with numerous studies proposing the use of ML to improve EDA methods. These studies cover almost all stages of the chip design process, including design space reduction and exploration, logic synthesis, placement, routing, testing, verification, manufacturing, etc. The special session on Machine Learning for EDA aims to apply ML techniques to accelerate EDA tasks. ML methods show great potential in generating high-quality solutions

Session Organizer : Prof. Rung-Ching Chen and Prof. Alex Long-Sheng Chen
Instituion : Chaoyang University of Technology
E-mail : crching@cyut.edu.tw , lschen@cyut.edu.tw

Deep Learning combines high-performance computing leading to unusual solutions for multi-model data analysis problems. Deep Learning-empowered systems can nowadays achieve performance levels in various data analysis tasks comparable to, or even exceeding, those of human beings. These advancements have the potential to open new high-impact applications in different environments. In this special issue, the authors will fully exploit Deep Learning solutions in smart applications through theoretical, methodological, and experimental contributions.

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