Abstract: The low voltage of many nonpolluting power sources necessitates ultra-high voltage gain dc-dc converters. This paper proposes a three-winding coupled inductor and voltage multiplier cell ultra-high voltage gain converter using interleave. Interleaving reduces filter…
Abstract: A modular inverter-based parallel multi-inverter system provides high and extendable power levels for inductive power transfer (IPT). Adjusting the number of paralleled inverters allows for modular power requirements. Parallel inverters use a master-slave scheme…
Abstract: High-power-density, high-efficiency power converters are still gaining popularity. High-frequency operation reduces power converter size, but magnetic components limit it. Widebandgap devices raise power converter switching frequencies to hundreds of kilohertz, enabling PCB winding planar…
Abstract: This letter proposes a three-level dc/dc converter for dc microgrid hybrid energy storage systems (HESS). One bidirectional converter integrates energy storage devices (ESDs) like batteries and ultracapacitors (UC). Due to three voltage levels, the…
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: Road intersections have always caused traffic congestion, but an efficient transportation system can benefit society. Real-time traffic signal timing may reduce such traffic congestion. Most traffic signal control methods require a lot of road…
Abstract: Autonomous Driving’s most important module is pedestrian detection. Cameras are often used for this, but their quality suffers in low-light nighttime driving. A thermal camera’s image quality is unaffected in similar conditions. This paper…
Abstract: Vehicle re-identification (Re-ID) research has grown due to intelligent traffic control and monitoring. Vehicle Re-ID is more difficult and unpredictable than person Re-ID because viewpoint variations greatly affect vehicle appearance. Existing studies mostly extract…
Abstract: Transport mode detection is a classification problem to design an algorithm to infer a user’s transport mode from multimodal signals (GPS and/or inertial sensors). It can track carbon footprints, analyze mobility behavior, and plan…
Abstract: Deep learning has improved short-term traffic forecasting. However, traffic flow stochasticity and distribution imbalance cause uncertainty and network overfitting during deep learning. This paper proposes M-B-LSTM, an end-to-end hybrid deep learning network model for…
Abstract: Many image understanding tasks require natural scene text spotting. Text detection and recognition are subtasks. We propose a unified network that localizes and recognizes text in a single forward pass without image cropping, feature…
Abstract: Understanding human-object interaction (HOI) requires detection. Interactiveness Knowledge—whether humans and objects interact—is examined in this paper. Interactiveness knowledge can be learned across HOI datasets and bridge diverse HOI category settings. We use an Interactiveness…
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