This paper presents a multidimensional analysis of Historic Building Information Modeling (HBIM) segmentation, offering a roadmap towards standardization, a key dimension towards broader adoption within the Cultural Heritage (CH) sector. HBIM faces m...
Cell migration is crucial in many processes of development and maintenance of multicellular organisms and it can also be related to disease, e.g., Cancer metastasis, when cells migrate to organs different to where they originate. A precise analysis o...
Optical image analysis is commonly used to characterize different feedstock material for ironmaking, such as iron ore, iron ore sinter, coal and coke. Information is often needed for phases which have the same reflectivity and chemical composition, b...
Background/Objectives: Accurate nuclear segmentation is a fundamental step in computational pathology, enabling reliable estimation of cellularity and nuclear morphology. However, segmentation models are typically evaluated under ideal imaging condit...
Interpretability has attracted increasing attention in earth observation problems. We apply interactive visualization and representation analysis to guide the interpretation of glacier segmentation models. We visualize the activations from a U-Net to...
This paper aims to conduct a statistical analysis of different components of nnU-Net models to build an optimal pipeline for lung nodule segmentation in computed tomography images (CT scan). This study focuses on semantic segmentation of lung nodules...
In medical diagnostics and decision-making, particularly in dentistry where structural interpretation of radiographs plays a crucial role, accurate image segmentation is a fundamental step. One established approach to segmentation is the use of clust...
As a fundamental but difficult topic in computer vision, 3D object segmentation has various applications in medical image analysis, autonomous vehicles, robotics, virtual reality, lithium battery image analysis, etc. In the past, 3D segmentation was...
Personal privacy on online social networks (OSN) is becoming increasingly important. The collection and misuse of personal information can affect people’s behavior and can have a broader impact on civil society. The aim of this paper is to expl...
Although great success has been achieved in instance segmentation, accurate segmentation of instances remains difficult, especially at object edges. This problem is more prominent for instance segmentation in remote sensing imagery due to the diverse...
Danmaku analysis is important for understanding video content and user interactions. However, current methods often look at separate comments and do not see the complex links between Danmaku and the video’s context. This paper presents a new ap...
This paper presents the mathematical framework of Recurrence Quantification Analysis (RQA) for dynamic video processing, exploring its applications in two primary tasks: scene change detection and adaptive foreground/background segmentation. Original...
Mineral image segmentation based on computer vision is vital to realize automatic mineral analysis. However, current image segmentation methods still cannot effectively solve the problem of sandstone grains that are adjoined and concealed by leaching...
This paper proposed a method for improving the XLNet model to address the shortcomings of segmentation algorithm for processing Chinese language, such as long sub-word lengths, long word lists and incomplete word list coverage. To address these issue...
In recent years, regional algorithms have shown great potential in the field of synthetic aperture radar (SAR) image segmentation. However, SAR images have a variety of landforms and a landform with complex texture is difficult to be divided as a who...
Robust gait segmentation is the basis for mobile gait analysis. A range of methods have been applied and evaluated for gait segmentation of healthy and pathological gait bouts. However, a unified evaluation of gait segmentation methods in Parkinson’s...
Accurate segmentation of retinal vessels is of great significance for computer-aided diagnosis and treatment of many diseases. Due to the limited number of retinal vessel samples and the scarcity of labeled samples, and since grey theory excels in ha...
Concrete arch dams represent a predominant dam type in water conservancy and hydropower projects in China. The control of concrete placement progress during construction directly impacts project quality and construction efficiency. Traditional manual...
Producers and retailers are the driving force behind the adoption of the idea of sustainability. It has been found that while preparing their product range offer, many still pay attention to the same set of criteria: size of the customers’ earn...
Digital twins are increasingly gaining popularity as a method for simulating intricate natural and urban environments, with the precise segmentation of 3D objects playing an important role. This study focuses on developing a methodology for extractin...
Plastic-covered greenhouse (PCG) segmentation represents a significant challenge for object-based PCG mapping studies due to the spectral characteristics of these singular structures. Therefore, the assessment of PCG segmentation quality by employing...
The aim of this study is to analyze the segmentation of participants in a sports event according to their perceived quality, perceived value, satisfaction, and future intentions, in order to better understand how each user profile behaves. The sample...
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To construct a litchi harvesting robot, the first key part is the machine vision system which is used to recognize ripe litchi clusters and their main fruit bearing branch. It selects and locates picking points. Hence, in order to establish a thresho...
Semantic segmentation in biological images is increasingly common, particularly in smart agriculture, where deep learning model precision is tied to image labeling quality. However, research has largely focused on improving models rather than analyzi...
The precise segmentation of different regions of the prostate is crucial in the diagnosis and treatment of prostate-related diseases. However, the scarcity of labeled prostate data poses a challenge for the accurate segmentation of its different regi...
Accurate behavioral segmentation of vessel trajectories from Automatic Identification System (AIS) is essential for maritime safety and traffic management. Existing methods often rely on predefined thresholds or emphasize geometric criteria and offer...
Digitization in pathology and cytology labs is now widespread, a significant shift from a decade ago when few doctors used image processing tools. Despite unchanged scanning times due to excitation in fluorescent imaging, advancements in computing po...
Despite the importance of a sustainable food system, prior research has not empirically examined whether general food sustainability perceptions and production-specific sustainability perceptions co-occur consistently across audience segments, which...
Smartphone-based proximal sensing has emerged as a promising low-cost approach for pasture monitoring. A critical component of this methodology is accurate leaf segmentation, as it directly affects the reliability of subsequent image-based analyses....
Many people have switched to gardening as their new hobby during the COVID-19 pandemic, including Filipinos. With its increasing popularity, Filipinos called the new hobbyists “plantitas” and “plantitos” instead of the old-fas...
This article presents a comprehensive evaluation of image segmentation methods for monitoring morphological changes in refugee camps, comparing five distinct approaches: ESRI Landviewer clustering, K-means clustering, U-Net segmentation, Meta’s...
The advent of very high resolution (VHR) satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA) have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is a...
Background/Objectives: Recent advancements in artificial intelligence (AI) have spurred interest in developing computer-assisted analysis for imaging examinations. However, the lack of high-quality datasets remains a significant bottleneck. Labeling...
Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous dri...
Nowadays, image analysis has a relevant role in most scientific and research areas. This process is used to extract and understand information from images to obtain a model, knowledge, and rules in the decision process. In the case of biological area...
In today’s data-driven business landscape, effective customer segmentation is crucial for enhancing engagement, loyalty, and profitability. Traditional clustering methods often struggle with datasets containing both numerical and categorical va...
An automatic temporal video segmentation framework is introduced in this article. The proposed cut detection technique performs a high-level feature extraction on the video frames, by applying a multi-scale image analysis approach combining nonlinear...
Positron Emission Tomography scan images are extensively used in radiotherapy planning, clinical diagnosis, assessment of growth and treatment of a tumor. These all rely on fidelity and speed of detection and delineation algorithm. Despite intensive...
Machine learning models based on radiomic features allow us to obtain biomarkers that are capable of modeling the disease and that are able to support the clinical routine. Recent studies have shown that it is fundamental that the computed features a...
Image segmentation and geographic object-based image analysis (GEOBIA) were proposed around the turn of the century as a means to analyze high-spatial-resolution remote sensing images. Since then, object-based approaches have been used to analyze a w...
The general population’s assessment and perception of a city can be influenced by its skyline, which is one of its representatives. This paper uses semantic segmentation and exploratory factor analysis to conduct a study from two different pers...
Accurate extraction of vegetation information from high-resolution remote sensing (RS) imagery is crucial for efficient urban ecological environment monitoring and land use management. However, due to the high cost of manual annotation in remote sens...
Understanding tourist behavior requires analytical frameworks capable of capturing both symmetric relationships among motivational constructs and asymmetric causal effects on behavioral intentions. Conventional segmentation approaches, particularly t...
Skin ulcers are open wounds on the skin characterized by the loss of epidermal tissue. Skin ulcers can be acute or chronic, with chronic ulcers persisting for over six weeks and often being difficult to heal. Treating chronic wounds involves periodic...
Background/Objectives: Precise stepping control is fundamental to human mobility, and impairments increase fall risk in older adults and individuals with neurological conditions. This study investigated the cortical networks underlying stepping accur...
The objective evaluation of Daqu cross-sectional quality is challenging due to its heterogeneous structure, small features, and low contrast. This study proposes a semantic-segmentation-based framework for the automated identification and quantitativ...
Quantitative microstructure evaluation of sedimentary rock thin sections is essential for revealing reservoir flow mechanisms and assessing reservoir quality. However, traditional manual identification is inefficient and prone to subjectivity. Althou...
Image-based analysis offers a scalable way to examine indoor environmental design, but semantic segmentation studies often stop at pixel-level recognition and provide limited design-oriented quantification. This study proposes the Interior Design Ele...
Compared to multispectral or panchromatic bands, fusion imagery contains both the spectral content of the former and the spatial resolution of the latter. Even though the Estimation of Scale Parameter (ESP), the ESP 2 tool, and some segmentation eval...
Crop field monitoring using unmanned aerial vehicles (UAVs) is one of the most important technologies for plant growth control in modern precision agriculture. One of the important and widely used tasks in field monitoring is plant stand counting. Th...
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