This paper proposes a collaborative framework to support task offloading in connected vehicular environments. The approach relies on the dynamic formation of temporary teams of connected vehicles in a mobile edge computing scenario. A novel trust mod...
The Global Positioning System (GPS) is not the only way to solve connected objects’ geo-localization problems; it is also possible to use the mobile network infrastructure to geo-locate objects connected to the network, using antennas and signals des...
Small object detection, which is frequently applied in defect detection, medical imaging, and security surveillance, often suffers from low accuracy due to limited feature information and blurred details. This paper proposes a small object detection...
Integrating electric vehicles (EVs) into a microgrid improves the efficiency, flexibility, and robustness of microgrids. Unfortunately, the uncertainties of EVs, in terms of their connection/disconnection times and their initial SOC values, make inte...
In this paper, a high precision detection method of salient objects is presented based on deep convolutional networks with proper combinations of shallow and deep connections. In order to achieve better performance in the extraction of deep semantic...
Object detection is an important task of remote sensing applications. In recent years, with the development of deep convolutional neural networks, object detection in remote sensing images has made great improvements. However, the large variation of...
Airborne speech enhancement is always a major challenge for the security of airborne systems. Recently, multi-objective learning technology has become one of the mainstream methods of monaural speech enhancement. In this paper, we propose a novel mul...
Multiple Object Tracking (MOT) aims to detect and track multiple targets across consecutive video frames while preserving consistent object identities. While appearance-based approaches have achieved notable success, they often struggle in challengin...
This paper evaluates data stream classifiers from the perspective of connected devices, focusing on the use case of Human Activity Recognition. We measure both the classification performance and resource consumption (runtime, memory, and power) of fi...
Longitudinal-connected air suspension has been proven to have desirable dynamic load-sharing performances for multi-axle heavy vehicles. However, optimization approaches towards the improvement of comprehensive vehicle performance through the geometr...
In weak grid, feedforward of grid voltage control is widely used to effectively suppress grid-side current distortion of inverters caused by harmonics in point of common coupling (PCC) voltage. However, due to its introduction of a positive feedback...
Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, re...
This paper presents best practices on how to design reminder objects. Reminder objects are digitally augmented everyday objects that break down and communicate complex information via sensory input and output. In the first section of this paper, we i...
The effects of corticomuscular connectivity during object manipulation tasks with different haptic sensations have not been quantitatively investigated. Connectivity analyses enable the study of cortical effects and muscle responses during movements,...
Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such a...
Forecasts announce that the number of connected objects will exceed 20 billion by 2025. Objects, such as sensors, drones or autonomous cars participate in pervasive applications of various domains ranging from smart cities, quality of life, transport...
Aiming at the impact of bearing bushes on the lubrication and friction and wear of diesel engine connecting rod big-end bearings, a certain type of diesel engine connecting rod big-end bearing bush was taken as the research object and a multi-body dy...
This paper is mainly devoted to studying the deployment problem of a multi-static radar system (MSRS) within a non-connected deployment region using multi-objective particle swarm optimization (MOPSO). By modeling and reformulating the problem, it ca...
This research proposes an efficient energy management system for standalone and grid-connected direct current (DC) distribution networks that consider photovoltaic (PV) generation sources. A complete nonlinear programming model is formulated to repre...
The assessment of grid-connected systems depends on their cost efficiency, reliability, and greenhouse gas (GHG) reduction potential. This study presents a multi-objective optimization framework for designing a grid-connected photovoltaic (PV) and ba...
With the development of deep learning, significant improvements and optimizations have been made in salient object detection. However, many salient object detection methods have limitations, such as insufficient context information extraction, limite...
Urbanization, driven by socio-economic development, has significantly impacted river ecosystems, particularly in plain city regions, leading to disruptions in river network structure and function. These changes have exacerbated hydrological fluctuati...
Objects thrown from tall buildings in communities are characterized by their small size, inconspicuous features, and high speed. Existing algorithms for detecting such objects face challenges, including excessive parameters, overly complex models tha...
Integrating connected and autonomous vehicle dedicated lanes (CAVDLs) into existing road networks under mixed traffic conditions presents a complex challenge, often requiring a balance of multiple conflicting objectives. This study develops a dynamic...
This study investigates the use of Autonomous Sensing Infrastructure and Connected and Autonomous Vehicles (CAV) technologies to support infrastructure-to-vehicle (I2V) and infrastructure-to-everything (I2X) communications, including the alerting of...
Recently, in the field of visual object tracking, visual object tracking algorithms combined with visual object segmentation have achieved impressive results while using mask to label targets in the VOT2020 dataset. Most of the trackers get the objec...
Previous studies have reported that a series of sensory–motor-related cortical areas are affected when a healthy human is presented with images of tools. This phenomenon has been explained as familiar tools launching a memory-retrieval process...
Formaldehyde and volatile organic compounds (VOCs) are major indoor pollutants with multiple origins. Standard methods exist to measure them that require analytical expertise and provide, at best, an average value of their concentrations. There is a...
Trajectory planning for intelligent connected vehicles (ICVs) must simultaneously address safety, efficiency, and environmental impact to align with sustainable development goals. This paper proposes a novel hierarchical trajectory planning framework...
This paper proposes a robust fabric defect detection method, based on the improved RefineDet. This is done using the strong object localization ability and good generalization of the object detection model. Firstly, the method uses RefineDet as the b...
As a typical component of remote sensing signals, remote sensing image (RSI) information plays a strong role in showing macro, dynamic and accurate information on the earth’s surface and environment, which is critical to many application fields...
The detection of distant tiny objects in aerial imagery plays a pivotal role in early warning, localization, and recognition tasks. However, due to the scarcity of appearance information, minimal pixel representation, susceptibility to blending with...
Vehicle-infrastructure cooperative perception is an ingenious way to eliminate environmental perception blind areas of connected and autonomous vehicles (CAVs). However, if the infrastructure transmits all environmental information to the nearby CAVs...
Built environment comprises of a multitude of complex networks of buildings and processes in and between buildings. The paper looks at resilience design on three different levels: the building, the site, and the region. The building resilience design...
Detecting and classifying real-life small traffic signs from large input images is difficult due to their occupying fewer pixels relative to larger targets. To address this challenge, we proposed a deep-learning-based model (Dense-RefineDet) that app...
Multi-modal object re-identification (ReID) is a challenging task that seeks to identify objects across different image modalities by leveraging their complementary information. Traditional CNN-based methods are constrained by limited receptive field...
Background: In this study, objects are used as a representation of relational wellbeing to help young refugees living in Norway, Scotland, and Finland to talk about important persons who make them feel well. At the time of this research, there is no...
With increasing numbers of computer vision and object detection application scenarios, those requiring ultra-low service latency times have become increasingly prominent; e.g., those for autonomous and connected vehicles or smart city applications. T...
Substations, as critical nodes for power transmission and distribution, play a pivotal role in ensuring the stability and security of the entire power grid. With the ever-increasing demand for electricity and the growing complexity of grid structures...
This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable e...
Long-term droughts observed in southern Australia have changed relationships between annual rainfall and runoff and tested some of the assumptions implicit in rainfall–runoff models used in these areas. Predictive confidence across these periods is w...
With the increase in the digitization efforts of herbarium collections worldwide, dataset repositories such as iDigBio and GBIF now have hundreds of thousands of herbarium sheet images ready for exploration. Although this serves as a new source of pl...
In this paper, a high-precision 3D object detector—Voxel–RCNN—is adopted as the baseline detector, and an improved detector named RCAVoxel-RCNN is proposed. To address various issues present in current mainstream 3D point cloud voxe...
Unmanned Aerial Vehicles (UAVs), also known as drones, are a class of aircraft without the presence of pilots on board. UAVs have the ability to reduce the time and cost of deliveries and to respond to emergency situations. Currently, UAVs are extens...
The road networks provide key information for a broad range of applications such as urban planning, urban management, and navigation. The fast-developing technology of remote sensing that acquires high-resolution observational data of the land surfac...
Objective: The shallow underwater environment is complex, with problems of color shift, uneven illumination, blurring, and distortion in the imaging process. These scenes are very unfavorable for the reasoning of the detection network. Additionally,...
High-resolution remote-sensing images cover more feature information, including texture, structure, shape, and other geometric details, while the relationships among target features are more complex. These factors make it more complicated for classic...
To address energy management challenges for intelligent connected automated range-extended electric vehicles under vehicle-road cooperative environments, a hierarchical energy management strategy (EMS) based on speed prediction is proposed from the p...
The progress of object detection technology is crucial for obtaining extensive scene information from aerial perspectives based on computer vision. However, aerial image detection presents many challenges, such as large image background sizes, small...
In recent years, advancements in Intelligent and Connected Vehicles (ICVs) have led to a significant increase in the amount of information to the driver through Human–Machine Interfaces (HMIs). To prevent driver cognitive overload, the developm...
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