Abstract: Autonomous driving and ADAS tasks are growing. However, porting multiple functions into a power-constrained computing device is difficult. This work aims to simplify the pixel-wise driving scene understanding learning process. This paper uses semantic…
Abstract: A real-time tracking algorithm using improved convolutional neural network (CNN) and transfer learning was proposed to improve image feature extraction, tracking time, and accuracy of traditional real-time algorithms for aerial vehicle traffic tracking. For…
Abstract: Facial phenotyping for medical prediagnosis has been successfully used to preclinically assess a variety of rare genetic diseases. Facial biometrics has rich links to underlying genetic or medical causes. This paper extends facial prediagnosis…
Abstract: To optimize on-street parking resources and create effective parking policies, parking occupancy data is essential. Advanced and expensive occupancy monitoring technologies often provide such data. Integrating bay-level occupancies and parking data from other systems…
Abstract: Noise and missing data corrupt medical data. In medical settings, missing patterns occur in bursts due to sensors being off or data being collected unevenly. Sequential variational autoencoders (VAEs) are proposed to model heterogeneous…
Abstract: Network slicing in vehicular networks could support emerging Vehicle-to-Vehicle (V2V) applications with diverse QoS requirements. However, time-varying V2V traffic and fast-changing network topology make network slicing in dynamic vehicular communications difficult. This paper proposes…
Abstract: The increased effective mini-batch size in large-scale distributed deep neural network training reduces generalization performance. Variations in learning rate and batch size over epochs and layers or batch normalization have been used to solve…
Abstract: Digital recommendation systems are crucial. They’re used in Spotify and Netflix. Physical exercise recommendation systems receive less research. Sedentary lifestyles cause many diseases and healthcare costs. This paper introduces a recommendation system that recommends…
Abstract: Hypertension and diabetes are diagnosed and monitored using retinal vasculature clues. Such conditions involve the microvascular system, which can only be seen in the retina. Recent advances in retinal imaging and computer vision have…
Abstract: Nearly 57 million people die annually, including over 2.7 million in the US. During the COVID-19 pandemic, institutions and government agencies use death reports to respond to communicable diseases. Even experienced doctors have trouble…
Abstract: Traditional traffic scene prediction methods use current observations to predict the future states of visible objects (not in blind spots). Based on current observations of visible objects, this study predicted the future states of…
Abstract: Physics-informed deep reinforcement learning (RL) is proposed for ATM aircraft conflict resolution. To enable optimal policy searching and human-explainable results for display and decision-making, the learning algorithm integrates prior physics understanding and model. First,…
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