A typical growth of cells inside tissue is normally known as a nodular entity. Lung nodule segmentation from computed tomography (CT) images becomes crucial for early lung cancer diagnosis. An issue that pertains to the segmentation of lung nodules i...
Anti-UAV surveillance demands real-time pixel-level UAV localization on resource-constrained gimbal-mounted platforms, yet existing lightweight segmentation models suffer from low recall that propagates to downstream tracking failure. Building on our...
The fiber-optic distributed acoustic sensor (DAS), which utilizes existing communication cables as its sensing media, plays an important role in urban infrastructure monitoring and natural disaster prediction. In the face of a wide, dynamic environme...
The up-to-date and information-accurate road database plays a significant role in many applications. Recently, with the improvement in image resolutions and quality, remote sensing images have provided an important data source for road extraction tas...
For the automation of Agrobacterium-mediated genetic transformation of tissue-cultured plantlets, accurate leaf vein segmentation is essential. The thin, low-contrast structure of leaf veins frequently leads to fragmented segmentation outputs, despit...
Precise medical image segmentation plays a vital role in disease diagnosis and clinical treatment. Although U-Net-based architectures and their Transformer-enhanced variants have achieved remarkable progress in automatic segmentation tasks, they stil...
The task of pitch estimation is an essential step in many audio signal processing applications. In this paper, we propose a data-driven pitch estimation network, the Dual Attention Network (DA-Net), which processes directly on the time-domain samples...
Temporal action localization (TAL) aims to predict action instance categories in videos and identify their start and end times. However, existing Transformer-based backbones focus only on global or local features, resulting in the loss of information...
Smartphone-based human activity recognition (HAR) uses features collected from smartphone sensors to distinguish between different human activities. The large number of correlated features generated by smartphone sensors can make feature selection an...
Defect recognition in ballastless track structures, based on distributed acoustic sensors (DASs), was researched in order to improve detection efficiency and ensure the safe operation of trains on high-speed railways. A line in southern China was sel...
Transcranial sonography (TCS) has been introduced to assess hyper-echogenicity in the substantia nigra of the midbrain for Parkinson’s disease (PD); however, its subjective and resource-demanding nature has impeded its widespread application. A...
Accurate bee counting is important for colony monitoring, pollination assessment, and precision beekeeping, but manual counting and dense point annotation are labor-intensive. This study proposes M3DANet, a lightweight semi-supervised density regress...
Semantic segmentation of 3D point clouds remains difficult when LiDAR or depth-camera data are sampled unevenly. This paper presents DANet, a 3D semantic segmentation framework built on joint density- and semantics-adaptive convolution. Its core oper...
Two-dimensional phase unwrapping (2-D PU) is vital for reconstructing Earth’s surface topography and displacement from interferometric synthetic aperture radar (InSAR) data. Conventional algorithms rely on the postulate, but this assumption is...
We propose restoring low-light images suffering from severe degradation using a deep-learning approach. A significant domain gap exists between low-light and real images, which previous methods have failed to address with domain alignment. To tackle...
Unmanned aerial vehicle (UAV) aerial object detection is increasingly important for traffic monitoring, emergency rescue, and environmental perception. However, vehicle detection in heavy rain, dense fog, blizzards, and backlit night scenes suffers f...
Salmonellosis is the second most commonly reported gastrointestinal infection in humans after campylobacteriosis, and an important cause of foodborne outbreaks in the EU/EEA. The vast majority (72.4%) of the salmonellosis foodborne outbreaks reported...
1 April 2022
Ensuring drug safety for pregnant women through prescription drug monitoring is essential. The aim of this study was to describe the prescription pattern of medicines among pregnant immigrant women from countries with high migratory pressure (HMPCs)...
Semantic segmentation of roads in remote-sensing images is a challenging task. This paper proposes a semantic segmentation model, DANet, for remote-sensing image road semantic segmentation. The model addresses the problems of missing, misclassificati...
The difficulty of classifying retinal fundus images with one or more illnesses present or missing is known as fundus multi-lesion classification. The challenges faced by current approaches include the inability to extract comparable morphological fea...
To reduce missed detections in LiDAR-based obstacle detection, this paper proposes a dual unmanned surface vessels (USVs) obstacle detection method using the MGNN-DANet template matching framework. Firstly, point cloud templates for each USV are crea...
Deep learning is a cutting-edge image processing method that is still relatively new but produces reliable results. Leaf disease detection and categorization employ a variety of deep learning approaches. Tomatoes are one of the most popular vegetable...
Micro-terrain recognition plays a crucial role in the planning, design, and safe operation of transmission lines. To achieve intelligent and automatic recognition of micro-terrain surrounding transmission lines, this paper proposes an improved semant...
The feeding behavior of dairy cows constitutes a complex temporal sequence comprising actions such as head lowering, sniffing, arching, eating, head raising, and chewing. Its precise recognition is crucial for refined livestock management. While exis...
Since pathological images have some distinct characteristics that are different from natural images, the direct application of a general convolutional neural network cannot achieve good classification performance, especially for fine-grained classifi...
Riverine–lacustrine ecosystems in river–lake continua face increasing threats, yet conventional vulnerability maps often overlook local degradation drivers. This study presents an advanced satellite-based mapping framework using Deep Atte...
High-precision landcover classification is a fundamental prerequisite for resource and environmental monitoring and land-use status surveys. Imbued with intricate spatial information and texture features, very high spatial resolution remote sensing i...
This study employed Deep Abstract Networks (DANets), independently and in combination with the Whale Optimization Algorithm (WOA), to generate high-resolution susceptibility maps for drought and wildfire hazards in the Oroqen Autonomous Banner in Inn...
Astrocytes are crucial in the regulation of neurotransmitter homeostasis, and while their involvement in the dopamine (DA) tripartite synapse is acknowledged, it necessitates a more comprehensive investigation. In the present study, experiments were...
Neuroendocrine tumors are uncommon in the gastrointestinal system but can develop in the majority of the body’s epithelial organs. Our goal was to examine the presence and clinical application of serum dopamine (DA), serotonin (ST), norepinephr...
Pine wilt disease has caused severe damage to China’s forest ecosystems. Utilizing the rich information from very-high-resolution (VHR) satellite imagery for large-scale and accurate monitoring of pine wilt disease is a crucial approach to curb...
Prolonged exposure to HIV-1 transactivator of transcription (Tat) protein dysregulates monoamine transmission, a physiological change implicated as a key factor in promoting neurocognitive disorders among people living with HIV. We have demonstrated...
Astrocytes actively participate in neurotransmitter homeostasis by bidirectional communication with neuronal cells, a concept named the tripartite synapse, yet their role in dopamine (DA) homeostasis remains understudied. In the present study, we inv...
Background/Objectives: Pituitary apoplexy (PA) is a rare medical emergency characterized by the sudden onset of symptoms resulting from hemorrhage and/or infarction within the pituitary gland. Precipitating factors include the use of dopamine agonist...
Drivable Area (DA) detection is crucial for autonomous driving. Camera-based methods rely heavily on illumination conditions and often fail to capture accurate 3D information, while LiDAR-based methods offer accurate 3D data and are less susceptible...
Purpose: High-throughput “-omic” technologies have enabled the detailed analysis of metabolic networks in several cancers, but NETs have not been explored to date. We aim to assess the metabolomic profile of NET patients to understand metabolic dereg...
Prolactinomas are the commonest form of pituitary neuroendocrine tumor (PitNET), representing approximately half of such tumors. Dopamine agonists (DAs) have traditionally been the primary treatment for the majority of prolactinomas, with surgery con...
Over the past five years, the proliferation of virtual reality platforms and the advancement of metahuman technologies have underscored the importance of natural interaction and emotional expression. As a result, there has been significant research a...
Circular-Scan photoacoustic tomography (PAT) can provide high-resolution images of optical absorption, but its analytical reconstructions, such as delay-and-sum (DAS), are highly sensitive to scanning radius (SR) inaccuracies, which cause severe geom...
The aggravation of left ventricular diastolic dysfunction (LVDD) could lead to ventricular remodeling, wall stiffness, reduced compliance, and progression to heart failure with a preserved ejection fraction. A non-invasive method based on convolution...
To promote the inheritance of traditional culture, a variety of emerging methods rooted in machine learning and deep learning have been introduced. Dunhuang patterns, an important part of traditional Chinese culture, are difficult to collect in large...
Accurately segmenting grape clusters and detecting grape varieties in orchards is beneficial for orchard staff to accurately understand the distribution, yield, growth information, and efficient mechanical harvesting of different grapes. However, fac...
Deep learning-based water body extraction methods generally focus on maximizing accuracy while neglecting inference speed, which can make them challenging to apply in real-time applications. To address this problem, this paper proposes a lightweight...
This research introduces a new method for creating synthetic Distributed Acoustic Sensing (DAS) datasets from transport microsimulation models. The process involves modeling detailed vehicle interactions, trajectories, and characteristics from the PT...
Hyperspectral image (HSI) classification benefits from rich spectral information; however, high dimensionality of HSI data increases computational cost, noise sensitivity, and the risk of overfitting when labeled samples are limited. Most pretrained...
In recent years, significant progress has been made in understanding that Parkinson’s disease (PD) is associated not only with the dopamine (DA) but also with the norepinephric (NE) system. In order to investigate the potential involvement of N...
Accurate retinal vessel segmentation supports quantitative vascular analysis in assessing ocular and systemic diseases. Yet, its clinical scalability is constrained by limited pixel-level annotations and domain shift across heterogeneous fundus datas...
Pituitary neuroendocrine tumors (PitNETs) represent one of the most common intracranial lesions. The pharmacological approach to PitNETs is mainly based on the use of somatostatin (SS) receptor ligands (SRLs) and dopamine agonists (DAs), although res...
Predicting dental development in individuals, especially children, is important in evaluating dental maturity and determining the factors that influence the development of teeth and growth of jaws. Dental development can be accelerated in patients wi...
We present here the organization of the recently-constituted da Vinci European BioBank (daVEB, https://www.davincieuropeanbiobank.org/it). The biobank was created as an infrastructure to support the activities of the Fiorgen Foundation (http://www.fi...
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