THE 28TH INTERNATIONAL COMPUTER SCIENCE AND ENGINEERING CONFERENCE 2024
THE 28TH INTERNATIONAL COMPUTER SCIENCE AND ENGINEERING CONFERENCE 2024
THE 28TH INTERNATIONAL COMPUTER SCIENCE AND ENGINEERING CONFERENCE 2024
Nowadays, AI techniques have been advancing and are being applied in many kinds of data, especially in video analytics. In this session, we aim to present many of our research works in real-time deep learning-based video analytics. First, DeepGI is our innovation to assist endoscopists in detecting anomalies in gastrointestinal (GI) tracts in real-time from various types of endoscopy videos. Our models can (i) detect polyps from colonoscopy videos to prevent colon cancer, (ii) segment gastric intestinal metaplasia (GIM) lesions from gastroscopy videos, and (iii) classify malignant scenes of bile duct strictures from cholangioscopy videos. Second, D-mind is an innovation from AI for Mental Health (AIMET) that helps detect depression from interview videos in real-time through a mobile application. At the moment, more than 200,000 users are using the D-mind application. Third, we can identify the severity level of Parkinson’s Disease (PD) patients using facial expression and gait videos. All of these works are good examples that theory in the AI domain can be applied in real-world applications.
Peerapon Vateekul received a Ph.D. degree from the Department of Electrical and Computer Engineering, University of Miami (UM), FL, USA, in 2012. Currently, he is an associate professor at the Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Thailand. His research interests include machine learning, data mining, deep learning, text mining, and big data analytics. To be more specific, his works include variants of classification, natural language processing, data quality management, video analytics, and applied deep learning and reinforcement learning techniques in various domains viz. healthcare, geoinformatics, hydrometeorology, transportation, and energy. Some examples of AI-assisted medical diagnoses are real-time polyp detection from colonoscopy videos, gastrointestinal metaplasia segmentation from gastroscopy videos, depressive scoring from interview videos, Parkinson’s face classification, and movement disorder diagnosis. He is a certified SAS instructor for more than 10 years. Moreover, he is also a certified instructor for NVIDIA Deep Learning Institute and has joined NVIDIA AI Technology Center (NVAITC) since 2018.
Living creatures can quickly form their gaits within minutes of being born. This is due to their neural locomotion control circuits comprising genetically encoded. They can quickly adapt their movement to traverse a variety of substrates and even take proactive steps to avoid colliding with an obstacle. Furthermore, in addition to locomotion, they can also perform diverse complex autonomous behaviors, such as object transportation and navigation, with a high degree of energy efficiency. Biological studies reveal that these capabilities are the result of the coupling of their biomechanics (e.g., structures, muscles, and materials) and neural mechanisms with plasticity and memory (brain).
In this talk, I will present “how we can realize biomechanics and neural mechanisms inspired by nature for robots so they can become more intelligent like living creatures”. I will also demonstrate that this nature-inspired robotics can help us not only address scientific questions, but also advance robotics technology for real world (industrial) applications. It may even bring the goal of creating “true robot intelligence” a little bit closer.
Poramate Manoonpong received a Ph.D. degree (Dr.-Ing.) in Electrical Engineering and Computer Science from the University of Hannover, Germany in 2006. Currently, he is an assistant professor at the Embodied AI & Neurorobotics Lab, School of Information Science and Technology (IST), Vidyasirimedhi Institute of Science and Technology (VISTEC), Thailand. His main research interests are bio-inspired robotics, neural locomotion control, embodied AI, biomechanics, and intelligent systems. He has published more than 100 papers in these areas. He serves as an associate editor for several robotics journals including IEEE Robotics and Automation Letters (RA-L) and Frontiers in Neurorobotics. He has been awarded several prestigious grants including a Thailand Research Fund (TRF) Senior Research Scholar, a Humboldt Research Fellowship for Experienced Researchers, and an ERC Starting Grant. Besides his academic achievements, he also contributes to industrial applications of robotics, including the development of inspection robots for the automotive industry and walking robots for agricultural applications. He is an IEEE Senior Member and a member of the International Society for Adaptive Behavior (ISAB) and the Society for Neuroscience (SfN).
