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Keynote Speakers
Non-Computable You: Hard Limits to What AI Can Do
Dr. Robert J. Marks
  • Distinguished Professor, Bayor University, USA
Abstract
Will machines eventually replace attorneys, physicians, computer programmers, and world leaders? What about composers, painters, and novelists? Will future supercomputers replicate and surpass human abilities? Are we merely meat computers destined to be outpaced by tomorrow’s ultra-powerful artificial intelligence? The answer is no. Just as math has its limitations—such as the impossibility of trisecting an angle with only a compass and straightedge—and physics has its boundaries—like the impossibility of perpetual motion—computers also face fundamental constraints. AI, both now and in the future, will never possess emotions, creativity, or understanding. These powers belong to another—to non-computable you.
Biography
Robert J. Marks Ph.D. is Distinguished Professor of Electrical and Computer Engineering at Baylor University. He is Senior Fellow and Director of the Bradley Center for Natural & Artificial Intelligence at Discovery Institute. Marks is a Fellow of both the Institute of Electrical and Electronic Engineers (IEEE) and Optica (formerly the Optical Society of America). He was the former Editor-in-Chief of the IEEE Transactions on Neural Networks and President of the IEEE Neural Networks Council (now the IEEE Computational Intelligence Society). Funded by such organizations as NIH, NSF, ARL, ONR, JPL and NASA. Marks and his colleagues have made contributions to applied algorithms and artificial/computational intelligence. They have applied the technology to sonar, forecasting, remote sensing, radar, spectrum sharing, antennas, radiometry, engine design and swarm science.
Marks is author of the books Non-Computable You: What You Do That Artificial Intelligence Never Will Never Do (Discovery Press), and Handbook of Fourier Analysis and Its Applications (Oxford University Press.) He is co-author of the books Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks (with Russ Reed - MIT Press) and For a Greater Purpose: The Life and Legacy of Walter Bradley (with William Dembski - Erasmus Press) . Marks is the recipient of a NASA Brief Award and has consulted for Microsoft, Boeing and DARPA.
Marks describes himself as a John 3:16 Christian. He served 17 years as faculty adviser for CRU at the University of Washington and is a co-faculty advisor to Ratio Christi at Baylor University.


Hybrid Wavelet-Attention Model for Detecting Changes in High-Resolution Remote Sensing Images
Dr. Wisnu Jatmiko
  • Professor, the University of Indonesia, Indonesia
Abstract
Change detection is a remote sensing task for detecting a change from two satellite imagery in the same area while being taken at different times. Change detection is one of the most difficult remote sensing tasks because the change to be detected (real-change) is mixed with apparent changes (pseudo-change) due to differences in the two images, such as brightness, humidity, seasonal differences, etc. The emergence of a Vision Transformer (ViT) as a new standard in Computer Vision, replacing Convolutional Neural Network (CNN), also shifts the role of CNN in the field of remote sensing. Although ViT can capture long-range interactions between image patches, its computational complexity increases the number of patches quadratically. One solution to reduce the computational complexity in ViT is to reduce the key and values matrices in the self-attention (SA) mechanism. However, this causes information loss resulting in a trade-off between the effectiveness and efficiency of the method. To solve the problem, we developed a new change detection method called WaveCD. WaveCD uses Wave Attention (WA) instead of SA. WA uses the Discrete Wavelet Transform (DWT) decomposition to reduce the key and values matrices. Besides reducing the data, DWT decomposition also serves to extract important features that represent images so that the initial data can be approximated through the Inverse Discrete Wavelet Transform (IDWT) process. On the CDD dataset, WaveCD outperforms the state-of-the-art CD method, SwinSUNet, by 12.3% on IoU and 7.3% on F1 score. While on the LEVIR-CD dataset, WaveCD outperforms SwinSUNet by 4% on IoU and 2.5% on F1 score.
Biography
Wisnu Jatmiko is one of the academic staff at the Faculty of Computer Science, head of Intelligent Robotics and System (IRoS) Laboratory, and Head of Artificial Intelligence Cluster Research at University of Indonesia (UI). Wisnu obtained his Bachelor of Engineering degree and Magister of Computer Science degree from University of Indonesia in 1997 and 2000, respectively. In 2007, Wisnu received his Dr. Eng. degree from Micro-Nano System Engineering, Nagoya University, Japan; and starting from September 2017, became a Professor at the UI Faculty of Computer Science.
Wisnu has held the mandate as Coordinator of the Master and Doctoral Program in Computer Science, in 2017-2020, and also as Research Manager at the Faculty of Computer Science, for two periods from 2009-2017 (Period I: 2009-2013 and Period II: 2013-2017). In organizational activities, he is actively involved as General Chair or Program Chair in the International Conference on Advanced Computer Science and Information Systems / ICACSIS (scopus indexed, this year is the thirteenth year) and International Workshop on Big Data and Information Security / IWBIS (scopus and dblp indexed, this year is the sixth year), from 2009 until now.
Besides being active in internal activities. Wisnu is also part of the IEEE Indonesia Section. Wisnu has served as Chair of The Institute of Electrical and Electronics Engineers (IEEE) Indonesia Section for the 2019 and 2020 periods. During his time with IEEE Indonesia Section, Wisnu made a significant contribution. Wisnu provided good services including popularizing IEEE to many people by organizing various activities for students, academics, and industry, and improving the quality of conferences in Indonesia. During this period of service, Wisnu received an award as "An outstanding member recruitment and retention performance award" for 2019 and 2020, from IEEE Center, USA. In 2020, the IEEE Indonesian Section received the Outstanding Section award for its achievements in the 'Reaching Locals' Project organized by the IEEE Asia-Pacific Region (R10). Currently, Wisnu is still active as an advisory board of IEEE Indonesia Section.
As a professor in Artificial Intelligence and Robotics, Wisnu is one of the most productive researchers in the Faculty of Computer Science. With maximum performance, Wisnu completed several research projects with management funds of more than 15 billion rupiah (in the last five years). To date, Wisnu has published around 250 publications in SCOPUS-indexed journals and proceedings. These publications have led him to reach H-index 24 in the SCOPUS database. In addition, Wisnu has also documented research results in books and teaching materials




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