Automated damage inspection of railway viaducts requires pixel-level identification of structural components and surface damage such as cracking and rebar exposure. A common assumption in bridge inspection is that damage segmentation improves when co...
To address the challenges of compressing large-scale, multi-channel temperature data from aluminum alloy heating furnaces—and the limitations of traditional methods in preserving fidelity for critical tasks like energy accounting and process pl...
3D non-rigid shape correspondence is significant but challenging in computer graphics, computer vision, and related fields. Although some deep neural networks have achieved encouraging results in shape correspondence, due to the complexity of the loc...
Accurate satellite component segmentation plays a fundamental role in numerous on-orbit perception tasks, including spacecraft pose estimation, autonomous robotic servicing, and space situational awareness. However, existing segmentation methods stil...
Semantic segmentation of railway point clouds is complicated by anisotropic sampling, large data volumes, and small components. This study develops an acquisition-aware processing and segmentation framework that combines structure-aware filtering (SC...
In the field of computer vision, segmenting a 3D object into its component parts is crucial to understanding its structure and characteristics. Much work has focused on 3D object part segmentation directly from point clouds, and significant progress...
This work addresses the challenge of video semantic segmentation, a critical component in applications such as autonomous driving. The primary aim was to explore the role of temporal awareness in video sequences and its impact on split computing. To...
Deep-learning models require large amounts of accurately labeled data. However, for medical image segmentation, high-quality labels rely on expert experience, and less-experienced operators provide noisy labels. How one might mitigate the negative ef...
In this research, we present the Spatial-Aware Transformer (SAT), an enhanced implementation of the Swin Transformer module, purposed to augment the global modeling capabilities of existing transformer segmentation mechanisms within remote sensing. T...
To address the limitations in the accuracy of current cerebral cortex structure segmentation methods, this study proposes an automatic segmentation network based on dynamic recalibration and region awareness. The network is an improved version of the...
Spacecraft component segmentation is one of the key technologies which enables autonomous navigation and manipulation for non-cooperative spacecraft in OOS (On-Orbit Service). While most of the studies on spacecraft component segmentation are based o...
Background/Objectives: Virtual Bronchoscopic Navigation is used to guide bronchoscopes toward peripheral pulmonary lesions, but broad clinical and research adoption remains limited by the cost of proprietary software and by segmentation failures in s...
Segmentation of the Optic Disc (OD) and Optic Cup (OC) boundaries in fundus images is a critical step for early glaucoma diagnosis, but accurate segmentation is challenging due to low boundary contrast and significant anatomical variability. To addre...
Accurate analysis of lesions in colonoscopic images is essential for computer-aided diagnosis. However, most existing methods are designed for single-lesion segmentation and assume a predefined lesion category, limiting their applicability in real-wo...
The accurate forecasting of key performance indicators (KPIs) is essential for enhancing the reliability and operational efficiency of engineering systems under increasingly complex security challenges. However, existing approaches often neglect the...
The colonoscopy procedure heavily relies on the operator’s expertise, underscoring the importance of automated polyp segmentation techniques in enhancing the efficiency and accuracy of colorectal cancer diagnosis. Nevertheless, achieving precis...
Background: Cardiac magnetic resonance (MRI) images often exhibit low contrast, anatomical variability, and indistinct boundaries, particularly in the myocardium (MYO) and right ventricle (RV). These challenges can reduce the reliability of both manu...
Rising energy costs and strict CO2 traceability regulations create demand for monitoring energy and CO2 emissions in manufacturing. This paper presents a framework for modelling component-wise energy models with deployable accuracy. In many factories...
The interpretation of optical and synthetic aperture radar (SAR) images in remote sensing is general for many tasks, such as environmental monitoring, marine management, and resource planning. Instance segmentation of optical and SAR images, which ca...
Accurate image segmentation is a fundamental requirement for fine-grained image analysis, providing critical support for applications such as medical diagnostics, remote sensing, and industrial fault detection. However, in complex industrial environm...
Accurate spinal cord segmentation is important for quantitative analysis of spinal cord magnetic resonance imaging, including measurement of cross-sectional area and diffusion-based microstructural characterization. In pathological conditions like ce...
19 May 2021
Phonological skills have been found to be strongly related to early reading and writing development. Accordingly, the aim of this study was to examine the extent to which the development of phonological awareness facilitates reading acquisition in st...
Reliable delineation of brain tumor boundaries in multimodal magnetic resonance imaging (MRI) remains challenging despite substantial advances in deep learning–based segmentation. Although modern encoder–decoder architectures achieve stro...
Accurate perception of overhead conductors is fundamental to autonomous unmanned aerial vehicle (UAV) inspection, trajectory planning, and collision avoidance in transmission corridors. Existing vision-based approaches predominantly formulate power-l...
This study aims to detect those segments among the Hungarian food consumers who are aware of the climate risks of their food consumption. In order to achieve this goal, a survey was conducted with the participation of Hungarian university students. D...
Industrial visual inspection requires not only accurate segmentation but also reliable and traceable decision making, since incorrect automatic refinements may lead to downstream manufacturing failures. Although segmentation foundation models achieve...
Semantic segmentation of laparoscopic images requires costly pixel-level annotations, which are often unavailable for real surgical data. This gives rise to an unsupervised domain adaptation scenario, where labeled synthetic images serve as the sourc...
Segmenting key components of space targets using Inverse Synthetic Aperture Radar (ISAR) images is an important interpretation task in space situational awareness. However, the scarcity of pixel-level annotated data, inter-class confusion caused by m...
Edible mushrooms represent a food with high nutritional properties, and their consumption has a positive effect on the health of consumers. The aim of the paper is to identify the behavior and preferences of consumers in the consumption of edible mus...
Retrogressive thaw slumps (RTSs) serve as key indicators of global climate change and also pose significant risks to critical infrastructure along the Qinghai–Tibet Engineering Corridor (QTEC). Accurate automatic segmentation of RTSs using Sent...
Medical images commonly exhibit low contrast, weak boundaries, and complex textures. In addition, significant semantic differences exist between deep-level semantic features and shallow-level detail features, posing challenges for multi-scale feature...
Small- and medium-sized landslides frequently occur in clusters and exhibit fragmented morphologies, irregular boundaries, and spectral characteristics similar to surrounding roads, bare soil, and sparsely vegetated surfaces, making their automated e...
Accurate teeth segmentation and orientation are fundamental in modern oral healthcare, enabling precise diagnosis, treatment planning, and dental implant design. In this study, we present a comprehensive approach to teeth segmentation and orientation...
Temporal action detection (TAD) aims to localize and recognize action instances in untrimmed videos, and serves as a key component in practical intelligent electronic systems such as smart video surveillance and real-time human–machine interact...
Robust LiDAR point cloud processing in dynamic outdoor environments, where movable objects such as vehicles and pedestrians introduce significant structural uncertainty, remains a key challenge for remote sensing and autonomous systems. This work add...
Accurate vegetation-soil segmentation is a key component of intelligent agricultural vision systems operating under limited computational resources. Existing CNN-based approaches generally improve segmentation accuracy by increasing network complexit...
Three-dimensional semantic segmentation is crucial for comprehending transmission line structure and environment. This understanding forms the basis for a variety of applications, such as automatic risk assessment of line tripping caused by wildfires...
With the continuous advancement of on-orbit services and space intelligence sensing technologies, the efficient and accurate identification of spacecraft components has become increasingly critical. However, complex lighting conditions, background in...
Background/Objectives: Functional tissue units (FTUs), including tertiary lymphoid structures (TLSs), blood vessels, and glands, encode localized immune, vascular, and epithelial organization in histopathology. Accurate quantification of these struct...
Building polygon extraction is a critical task in remote sensing analysis and a fundamental component of modern urban management. Conventional segmentation-based methods often suffer from geometric distortions during the conversion from masks to poly...
Ischemic Heart Disease (IHD) is the leading cause of cardiovascular mortality worldwide. Early detection of ischemic changes using electrocardiogram (ECG) signals is vital for timely intervention and enhanced clinical outcomes. However, the diagnosis...
Crime forecasting in heterogeneous urban contexts remains challenging due to the combined effects of territorial heterogeneity and complex temporal dynamics. However, a large portion of the existing literature tends to address territorial segmentatio...
Accurate detection of internal defects in concrete structures is critical to structural safety. This study proposes a three-stage method for segmentation and geometric quantification of defects from 3D ultrasonic point clouds to support non-destructi...
RGB-T semantic segmentation fuses visible (RGB) and thermal infrared (TIR) images to enhance model robustness under complex lighting conditions. However, most existing methods employ unified fusion strategies in the spatial domain, limiting their abi...
Domain shifts pose significant challenges for cross-domain semantic segmentation in high-resolution remote sensing imagery. Inspired by the cognitive mechanisms of the human brain, we propose a Brain-Inspired Style Transfer and Semantic Segmentation...
The performance of deep-learning-based segmentation models is strongly dependent on the quality of the input data, which is frequently heterogeneous or degraded in real-world medical imaging scenarios. This work presents a data-centric algorithmic pi...
Accurate semantic segmentation of high-resolution images captured by unmanned aerial vehicles (UAVs) is crucial for applications in environmental monitoring, urban planning, and precision agriculture. However, challenges such as class imbalance, smal...
Medical image segmentation is a critical task in computer-assisted diagnosis, but accurate delineation remains challenging in sensor-captured dermoscopic and endoscopic images because of low contrast, blurred boundaries, acquisition artifacts, and la...
Super-pixels represent perceptually similar visual feature vectors of the image. Super-pixels are the meaningful group of pixels of the image, bunched together based on the color and proximity of singular pixel. Computation of super-pixels is highly...
Automated font generation for complex, compositional scripts like Korean Hangul presents a significant challenge due to the 11,172 characters and their complicated component-based structure. While existing component-based methods for font image gener...
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