Despite the rapid advances in deep learning (DL) for object detection, existing techniques still face several challenges. In particular, object detection in adverse weather conditions (AWCs) requires complex and computationally costly models to achie...
In order to reach the highest level of automation, autonomous vehicles (AVs) are required to be aware of surrounding objects and detect them even in adverse weather. Detecting objects is very challenging in sandy weather due to characteristics of the...
Satellite remote sensing provides a potential technology for detecting fog at dawn and dusk on a large scale. However, the spectral characteristics of fog at dawn and dusk are similar to those of the ground surface, which makes satellite-based fog de...
Object detection under adverse weather conditions remains a challenging problem for autonomous driving systems due to image degradation caused by rain, snow, haze, and complex illumination. Although RT-DETR achieves a good balance between detection a...
The prediction of drug–target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper,...
Human health is part of an interdependent multifaceted system. More than ever, we have increasingly large amounts of data on the body, both spatial and non-spatial, its systems, disease and our social and physical environment. These data have a geosp...
Clarifying the distribution pattern and overlapping relationship of sympatric relative species in the spatio-temporal niche is of great significance to the basic theory of community ecology and integrated management of multi-species habitats in the s...
For autonomous driving, perception is a primary and essential element that fundamentally deals with the insight into the ego vehicle’s environment through sensors. Perception is challenging, wherein it suffers from dynamic objects and continuou...
Deep learning-based classification and detection algorithms have emerged as a powerful tool for vehicle detection in intelligent transportation systems. The limitations of the number of high-quality labeled training samples makes the single vehicle d...
Recognizing and categorizing items in weather-adverse environments poses significant challenges for autonomous vehicles. To improve the robustness of object-detection systems, this paper introduces an innovative approach for detecting objects at diff...
The dawn of Artificial intelligence (AI) in healthcare stands as a milestone in medical innovation. Different medical fields are heavily involved, and pediatric emergency medicine is no exception. We conducted a narrative review structured in two par...
Robust object detection and weather classification are essential for the safe operation of autonomous vehicles (AVs) in adverse weather conditions. While existing research often treats these tasks separately, this paper proposes a novel multi objecti...
A web-based search system recommends and gives results such as customized image or video contents using information such as user interests, search time, and place. Time information extracted from images can be used as a important metadata in the web...
Object detection for autonomous vehicles under adverse weather conditions—such as rain, fog, snow, and low light—remains a significant challenge due to severe visual distortions that degrade image quality and obscure critical features. Th...
At the dawn of the 10V or big data data era, there are a considerable number of sources such as smart phones, IoT devices, social media, smart city sensors, as well as the health care system, all of which constitute but a small portion of the data la...
Mass wasting, as one of the most significant geomorphological processes, contributes immensely to planetary landscape evolution. The frequency and diversity of mass wasting features on any planetary body also put engineering constraints on its roboti...
Detecting and counting on road vehicles is a key task in intelligent transport management and surveillance systems. The applicability lies both in urban and highway traffic monitoring and control, particularly in difficult weather and traffic conditi...
Rain, snow, fog, and dust can degrade road-scene images, blur fine details, and consequently reduce the reliability of perception systems for autonomous driving. To address this problem, this paper proposes PF-ConvNeXt, an adverse weather recognition...
The Astrophysical Multimessenger Observatory Network (AMON) was founded to tie the world’s high-energy and multimessenger observatories into a single network, with the purpose to enable the discovering of multimessenger sources, to exploit these sour...
Robust and precise visual localization over extended periods of time poses a formidable challenge in the current domain of spatial vision. The primary difficulty lies in effectively addressing significant variations in appearance caused by seasonal c...
The COVID-19 global pandemic caused by the widespread transmission of the novel coronavirus (SARS-CoV-2) has become one of modern history’s most challenging issues from a healthcare perspective. At its dawn, still without a vaccine, contagion contain...
1 March 2024
Background: In response to the escalating global concerns surrounding skin cancer, this study aims to address the imperative for precise and efficient diagnostic methodologies. Focusing on the intricate task of eight-class skin cancer classification,...
Weather detection systems (WDS) have an indispensable role in supporting the decisions of autonomous vehicles, especially in severe and adverse circumstances. With deep learning techniques, autonomous vehicles can effectively identify outdoor weather...
The Open Radio Access Network (O-RAN) paradigm promises unprecedented flexibility and cost efficiency for 6G networks but introduces critical security risks due to its disaggregated, AI-driven architecture. This paper proposes a secure optimization f...
Dendrobium species are valuable medicinal and ornamental orchids whose epiphytic or lithophytic growth exposes them to fluctuating water availability. Comparative evidence on their carbon-assimilation strategies can help identify physiological traits...
Recent advancements in computer vision technology, developments in sensors and sensor-collecting approaches, and the use of deep and transfer learning approaches have excelled in the development of autonomous vehicles. On-road vehicle detection has b...
Images captured in rainy weather conditions often suffer from contamination, resulting in blurred or obscured objects, which can significantly impact detection performance due to the loss of identifiable texture and color information. Moreover, the q...
With the development of intelligent manufacturing and smart logistics, automated guided vehicles (AGVs) are gradually expanding from traditional indoor environments to factory roads, logistics parks, industrial parks, and other outdoor road environme...
Along with the advancement of light-weight sensing and processing technologies, unmanned aerial vehicles (UAVs) have recently become popular platforms for intelligent traffic monitoring and control. UAV-mounted cameras can capture traffic-flow videos...
Reliable visual detection of small floating objects on the water surface is a prerequisite for environmental monitoring and clean-up tasks performed by unmanned surface vehicles (USVs) on inland waterways. Such scenes are routinely degraded by low il...
As the need to discovers new mineral deposits and occurrences has intensified in recent years, it has become increasingly apparent that we need to map potentials via integrated information on the basis of metallogeny. Occurrences of mineralization su...