Topics

<> uav failures (1) <> UAV for Wireless Communications (1) <> UAV Security (1) <> UAV-Assisted (1) <> UAV-Assisted Cellular and Sensor Networks (1) <> UAV-based communications (1) <> UAV-enabled wireless communications (1) <> UAVs (1) <> ultra low power CMOS logic devices (1) <> ultra-low power circuit design (1) <> Ultra-Massive MIMO (1) <> Ultra-wide band Fractal Antennas (1) <> ultra-wideband (1) <> ultrasound ranging (1) <> Ultraviolet (1) <> ultraviolet detection (1) <> Ultrawide bandwidth wireless communication systems (1) <> Understanding Lab (1)

Research at the Image and Video Understanding Lab (IVUL) - Graduate Seminar - ECE

-

KAUST

In this talk, I will give an overview of research done in the Image and Video Understanding Lab (IVUL) at KAUST. At IVUL, we work on topics that are important to the computer vision (CV) and machine learning (ML) communities, with emphasis on three research themes: Theme 1 (Video Understanding): We aim to extract meaningful semantic information from large-scale video data by tackling research problems such as object tracking, activity detection, moment retrieval, and language grounding in video. Theme 2 (Visual Computing for Automated Navigation): We develop methodology to enable more accurate, reliable, and robust perception of the visual world for automated navigation applications (e.g. self-driving cars and UAVs). In this theme, we tackle research problems such as object tracking, segmentation, and detection in 3D data, as well as transfer learning from simulation (sim2real). Theme 3 (Fundamentals/Foundations): In this theme, we tackle fundamental research problems in CV and ML that transcend specific applications with focus on deep network theory/analysis (e.g. robustness, certification, and interpretability) and structured optimization methods for large-scale CV/ML problems. Throughout the talk, I will highlight some of the interesting projects at IVUL to encourage students to get interested in the research field.
<> underwater acoustic localization (1) <> underwater camera (1) <> Underwater sensor networks (1) <> Underwater target detection and localization (1) <> Underwater Vehicles (1) <> Underwater Video (1) <> underwater video transmission (1) <> underwater wireless optical networks (1) <> Unit commitment, Renewable integration, Quantum computing for power systems, Stochastic AC Optimal Power Flow, Grid-forming & grid-following inverters, HVDC design, Machine learning for power systems (1) <> universal robot (1) <> university of jeddah (1) <> University of Liverpool (1) <> University of Oxford (1) <> Unmanned Aerial Vehicle (1) <> unproven (1) <> untrimmed classification (1) <> Urban Air Management (1) <> urban architecture (1) <> URLLC (1) <> UV Emitter (1) <> UV LED (1) <> UWB channel impulse response estimation. (1) <> V2X (1) <> Vehicle-to-vehicle communications (1) <> Vehicular Communications (1) <> vehicular monitoring (1) <> Vehicular networks and intelligent transportation systems (1) <> vehicular tracking (1) <> Video (1)

Research at the Image and Video Understanding Lab (IVUL) - Graduate Seminar - ECE

-

KAUST

In this talk, I will give an overview of research done in the Image and Video Understanding Lab (IVUL) at KAUST. At IVUL, we work on topics that are important to the computer vision (CV) and machine learning (ML) communities, with emphasis on three research themes: Theme 1 (Video Understanding): We aim to extract meaningful semantic information from large-scale video data by tackling research problems such as object tracking, activity detection, moment retrieval, and language grounding in video. Theme 2 (Visual Computing for Automated Navigation): We develop methodology to enable more accurate, reliable, and robust perception of the visual world for automated navigation applications (e.g. self-driving cars and UAVs). In this theme, we tackle research problems such as object tracking, segmentation, and detection in 3D data, as well as transfer learning from simulation (sim2real). Theme 3 (Fundamentals/Foundations): In this theme, we tackle fundamental research problems in CV and ML that transcend specific applications with focus on deep network theory/analysis (e.g. robustness, certification, and interpretability) and structured optimization methods for large-scale CV/ML problems. Throughout the talk, I will highlight some of the interesting projects at IVUL to encourage students to get interested in the research field.
<> video-language grounding (1) <> virtual lab (1) <> virtual reality (1) <> virtual sensors (1) <> viscoelastic models (1) <> Visible (1) <> Visible LEDs (1) <> Visible light emitting diodes for next generation displays (1) <> Vision Foundation Models (1) <> Vision2030 (1) <> Visual (1)

Advancing Visual Intelligence via Neural System Design

-

KAUST

Building intelligent visual systems is essential for the next generation of artificial intelligence systems. It is a fundamental tool for many disciplines and beneficial to various potential applications such as autonomous driving, robotics, surveillance, augmented reality, to name a few. An accurate and efficient intelligent visual system has a deep understanding of the scene, objects, and humans. It can automatically understand the surrounding scenes. In general, 2D images and 3D point clouds are the two most common data representations in our daily life. Designing powerful image understanding and point cloud processing systems are two pillars of visual intelligence, enabling the artificial intelligence systems to understand and interact with the current status of the environment automatically. In this talk, I will first present our efforts in designing modern neural systems for 2D image understanding, including high-accuracy and high-efficiency semantic parsing structures, and unified panoptic parsing architecture. Then, we go one step further to design neural systems for processing complex 3D scenes, including semantic-level and instance-level understanding. Further, we show our latest works for unified 2D-3D reasoning frameworks, which are fully based on self-attention mechanisms. In the end, the challenges, up-to-date progress, and promising future directions for building advanced intelligent visual systems will be discussed.
<> Visual Language Models (1) <> VLSI (1) <> volume integral equation (1) <> Wasserstein distance (1) <> Water (1) <> water resources monitoring (1) <> Wave functional materials (1) <> Wavefront Sensing (1) <> waves (1) <> Waves Functional Materials (1) <> wearable wireless communication (1) <> web development (1) <> Web Security (1) <> Web Technologies (1) <> Wellbore (1) <> WEP Poster Competition (1) <> Wideband terahertz communications (1) <> WiDS (1) <> wiley (1) <> wind (1) <> Wind Farms (1) <> Wireless big data analysis (1) <> Wireless Communication and Signal Processing (1) <> wireless communications. (1) <> Wireless electronics (1) <> Wireless Energy Transfer (1) <> Wireless localization (1) <> wireless monitor (1) <> wireless monitoring (1) <> Wireless Optical Sensing (1) <> wireless power transfer design (1) <> wireless resource virtualization (1) <> Wireless Security through Optical Channels (1) <> Wireless sensors (1) <> Wireless sensors design (1) <> Wireless Systems (1) <> Wireless Technology (1) <> wireless telecommunication technology (1) <> Wireless Underground Sensor Networks (1) <> Young Scholar Awards (1) <> ​Dynamic spectrum access and cognitive radio networks (1) <> ​Radio Frequency Integrated Circuit (1)