Abstract: Globally, shared e-mobility services have been tested and integrated into modern urban planning. This paper addresses a practical but crucial issue in those systems: how to deploy and manage their infrastructure across space and…
Abstract: Smart roads can benefit from video analytics to automatically detect abnormalities. Vehicle detection is the first step, and any error will affect subsequent steps. In smart road environments, video analysis is often performed directly…
Abstract: Train delay prediction helps dispatchers estimate the train’s running state and make better dispatching decisions. Passenger flow, fault, extreme weather, and dispatching strategy affect train delays. Dispatcher strategy and knowledge limit train departure times….
Abstract: Head pose estimation is crucial for gaze estimation and attention modeling. Head pose indicates drowsiness, distraction, and attention in drivers. It can also control in-car infotainment systems. In controlled environments, computer vision algorithms using…
Abstract: Without a cure, stroke is the leading cause of death and disability worldwide. Deep learning-based stroke risk prediction models can outperform existing models with large, well-labeled data. Stroke data is usually split among hospitals…
Abstract: A well-designed vehicular ad hoc network (VANET) is essential to building a smart transportation system that supports traffic safety and high-efficiency transportation. VANETs’ dynamicity and infrastructure-less nature make them vulnerable to malicious nodes that…
Abstract: Large disparity and the non-Lambertian effect challenge light field (LF) reconstruction. Typical approaches either solve the large disparity challenge with depth estimation followed by view synthesis or avoid explicit depth information to enable non-Lambertian…
Abstract: Due to the abundance of imagery and non-imagery-based clinical data, dental AI is promising. Dental radiograph analysis by a specialist can aid clinical diagnosis and treatment. In recent years, Convolutional Neural Networks have achieved…
Abstract: ReID is difficult due to person images’ large pose variations and misalignment errors. Existing works use pose estimation, part segmentation, etc. to improve pedestrian representations. Boosting ReID accuracy requires computational overheads and makes deep…
Abstract: Extreme low-light visibility enhancement is difficult. Due to low SNR, image denoising methods may fail in near-darkness. In this paper, we study CMOS photosensor imaging pipeline noise statistics and develop a comprehensive noise model…
Abstract: E-health is growing due to the pandemic and personal healthcare awareness. In many e-health analytics applications, machine learning models improve medical diagnosis. However, in classic cloud-based/centralized e-health paradigms, all data is centrally stored on…
Abstract: Long-term traffic predictions are less dense than short-term ones. City-scale traffic prediction literature is also scarce due to data scarcity. This study examines the scalability of deep learning models for long-term large-scale traffic prediction….
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