Abstract: We propose a novel Convolutional Neural Network (CNN) architecture for joint detection and matching of feature points in images from different sensors using a single forward pass. Unlike classical approaches (SIFT, etc.), the feature…
Abstract: This study develops a high accident risk prediction model to analyze traffic accident data and prioritize intersection improvements. A traffic accident database was organized and analyzed, and an intersection accident risk prediction model based…
Abstract: Vision-based intelligent systems like driver assistance and transportation should consider weather. Haze in images can endanger drivers. Real-world haze density measures image visibility and usability. In outdoor vision-based intelligent systems, haze density prediction can…
Abstract: Many visual tasks use channel attention mechanisms to improve performance. It boosts informative channels and suppresses useless ones. Channel attention modules have been proposed and implemented recently. They rely on convolution and pooling. This…
Abstract: Existing vehicle re-identification methods use spatial pooling operations to aggregate feature maps extracted from off-the-shelf backbone networks like VGGNet, GoogLeNet, and ResNet. They neglect feature map spatial significance, lowering vehicle re-identification performance. First, an…
Abstract: Diabetes ICU patients have a higher risk of complications and in-hospital death. Due to many factors, estimating death risk is difficult and time-consuming. Healthcare providers want to identify high-risk ICU patients to reduce risk…
Abstract: Due to its many real-world applications—evacuation situation analysis, intelligent transport system deployment, traffic operations—human trajectory forecasting has been a field of active research for decades. We model human trajectory forecasting as learning a representation…
Abstract: With the development of various sensors in smartphones or wearable devices, human activity recognition (HAR) has been widely researched and has many applications in healthcare, smart cities, etc. Sensor-based HAR uses many hand-crafted feature…
Abstract: Smart traffic management systems forecast traffic. Missing data issues hinder urban road network traffic flow forecasting due to the widespread use of massive vehicle trajectory data. This paper investigates urban network-wide short-term traffic speed…
Abstract: Human-centric computer vision tasks require pedestrian detection, which is difficult. Handcrafted and deep features have improved over the past decade. We review recent pedestrian detection advances. We first review single-spectral pedestrian detection using handcrafted…
Abstract: Due to its importance in airline and airport efficiency, flight delay prediction has become popular. Most predictions use the single-airport scenario, which ignores airport networks’ time-varying spatial interactions. This paper examines flight delay prediction…
Abstract: Traffic flow prediction is essential to intelligent transportation systems and various traffic-related applications. Urban residents depend on fixed-route buses, which creates latent travel regularity. This fixed mobility mode hides human mobility patterns, particularly bus…
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