Indoor space is a core part of supporting indoor applications. Most of the existing indoor space models are expressed from three space scales: building, floor, and room, and the granularity is not fine enough, lacking the expression of each functiona...
Room segmentation is a basic task for the semantic enrichment of point clouds. Recent studies have mainly projected single-floor point clouds to binary images to realize two-dimensional room segmentation. However, these methods have difficulty solvin...
White blood cell (WBC) segmentation, which is important for cytometry, is a challenging issue because of the morphological diversity of WBCs and the complex and uncertain background of blood smear images. This paper proposes a novel method for the nu...
Indoor space segmentation is essential for indoor navigation, 3D reconstruction, and Building Information Modeling (BIM). However, reliable segmentation from unstructured 3D point clouds remains challenging due to structural voids caused by occlusion...
Internal waves (IWs) play a crucial role in the transport of energy and matter within the ocean while also posing significant risks to marine engineering, navigation, and underwater communication systems. Consequently, effective segmentation methods...
A novel interactive maintenance method for space station in-orbit devices using scene semantic segmentation technology is proposed. First, a wearable and handheld system is designed to capture images from the astronaut in the space station’s fr...
As a multimodal fusion task, audio-visual segmentation (AVS) aims to locate sounding objects at the pixel level within a given image. This capability holds significant importance and practical value in applications such as intelligent surveillance, m...
Open-vocabulary semantic segmentation aims to label each pixel of an image based on text descriptions provided at inference time. Recent approaches for this task are based on methods which require two stages: the first one uses a mask generator to ge...
Rice seedling segmentation is a fundamental process of extracting the guidance line for automated rice transplanters with a visual navigation system, which can provide crop row information to ensure the transplanter plants seedlings along the crop ro...
Crack segmentation is crucial for health monitoring and preventive maintenance of concrete structures. However, the complex morphologies of cracks and the limited resources of mobile devices pose challenges for accurate and efficient segmentation. To...
At the neighborhood scale, recognizing urban community green space (UCGS) is important for residential living condition assessment and urban planning. However, current studies have embodied two key issues. Firstly, existing studies have focused on la...
Agricultural robots and unmanned farmland management require real-time and precise parsing of crop leaves at the edge to support variable application of pesticides, seedling condition monitoring, and phenotypic analysis. However, the field environmen...
In the vision system of apple-picking robots, the main challenge is to rapidly and accurately identify the apple targets with varying halation and shadows on their surfaces. To solve this problem, this study proposes a novel, multi-feature, patch-bas...
In remote sensing image processing, cloud and cloud shadow detection is of great significance, which can solve the problems of cloud occlusion and image distortion, and provide support for multiple fields. However, the traditional convolutional or Tr...
This study evaluated reliability and accuracy of interproximal space measurement in two different orthodontic tooth-segmentation programs in comparison with clinical space measurement and assessed the minimum distance threshold ensuring accuracy. Fro...
Pedestrian-level semantic segmentation supports autonomous mobility, assistive navigation, and safety-oriented perception in public spaces. However, widely used urban segmentation datasets predominantly adopt vehicle-centered viewpoints that differ f...
Rapid and reliable landslide mapping from satellite observations is essential for hazard assessment, emergency response, and reservoir-area risk management, yet automatic segmentation remains challenging in mountainous regions because landslide scars...
LiDAR serves as the primary sensor for acquiring environmental information in intelligent driving systems. However, under adverse weather conditions, point cloud signals obtained by LiDAR suffer from intensity attenuation and noise interference, lead...
To accurately identify slope hazards based on high-resolution remote sensing imagery, an improved watershed segmentation algorithm is proposed. The color difference of the Luv color space was used as the regional similarity measure for region merging...
State-space models segment images in linear time, but existing dermoscopic segmenters serialize the two-dimensional feature map along only one or two scan directions and operate purely in the spatial domain, which dilutes the orientation cues and fin...
Remote sensing image segmentation requires balancing global context and local detail across multi-scale objects. However, convolutional neural network (CNN)-based methods struggle to model long-range dependencies, while transformer-based approaches s...
Urban green spaces (UGS) play a crucial role in the urban environmental system by aiding in mitigating the urban heat island effect, promoting sustainable urban development, and ensuring the physical and mental well-being of residents. The utilizatio...
Rock detection on the surface of celestial bodies is critical in the deep space environment for obstacle avoidance and path planning of space probes. However, in the remote and complex deep environment, rocks have the characteristics of irregular sha...
Fine-grained segmentation of Gyrodactylus opisthaptoral hard structures is challenging because of small targets, weak boundaries, local deformation, and debris interference. Using 175 microscopy images at a resolution of
Accurate cloud and cloud-shadow segmentation is a crucial step in optical remote sensing image preprocessing, playing a significant role in subsequent applications such as land-cover classification and change detection. However, the complexity of clo...
Accurate volumetric quantification of brain tumor subregions in magnetic resonance imaging (MRI) is sensitive to local prediction bias, because boundary over-expansion, missed enhancing foci, and class confusion at subregion transitions can propagate...
Semantic segmentation of urban meshes plays an increasingly crucial role in the analysis and understanding of 3D environments. Most existing large-scale urban mesh semantic segmentation methods focus on integrating multi-scale local features but stru...
In the field of remote sensing image segmentation, achieving high accuracy and efficiency in diverse and complex environments remains a challenge. Additionally, there is a notable imbalance between the underlying features and the high-level semantic...
The mapping and monitoring of urban green space (UGS) are of great significance for ecological assessment and sustainable development in urban settlements. However, for fine-grained classification tasks in high-resolution remote sensing imagery, exis...
Medical image segmentation is essential for clinical diagnosis and treatment planning. Despite the notable performance of convolutional neural networks (CNNs), they encounter difficulties in capturing long-range relationships crucial for precise boun...
Camellia oleifera is a crop of high economic value, yet it is particularly susceptible to various diseases and pests that significantly reduce its yield and quality. Consequently, the precise segmentation and classification of diseased Camellia leave...
In order to improve the shortcomings of the traditional constant section and gradual section space elevator system, combined with the advantages of constant section and gradual section space elevator system, a model of segmented space elevator system...
The space elevator system is a space tether system used to solve low-cost space transportation. Its high efficiency, large load and other characteristics have broad application prospects in the aerospace field. The stability analysis is the foundatio...
The relative pose estimation of the space target is indispensable for on-orbit autonomous service missions. Line segment detection is an important step in pose estimation. The traditional line segment detectors show impressive performance under suffi...
In recent years, many agriculture-related problems have been evaluated with the integration of artificial intelligence techniques and remote sensing systems. The rapid and accurate identification of apple targets in an illuminated and unstructured na...
Image-based line segment extraction plays an important role in a wide range of applications. Traditional line segment extraction algorithms focus on the accuracy and efficiency, without considering the integrity. Serious line segmentation fracture pr...
This study addresses a fundamental shortcoming in conventional dynamic stability analyses of space trusses: traditional rod elements or unsegmented beam models fail to capture member buckling under severe seismic excitation, often mischaracterizing s...
This paper proposes an efficient segmentation of the preretinal area between the inner limiting membrane (ILM) and posterior cortical vitreous (PCV) of the human eye in an image obtained with the use of optical coherence tomography (OCT). The researc...
The segmentation of the left ventricle endocardium (LVendo) and the left ventricle epicardium (LVepi) in echocardiography plays an important role in clinical diagnosis. Recently, deep neural networks have been the most commonly used approach for echo...
The Chongming Dongtan wetland, a representative coastal wetland in East Asia, faces a significant ecological threat from the invasive species Spartina alterniflora. The mixed ecotone formed between this invasive species and the native Phragmites aust...
Continuum robots (CRs) exhibit high compliance and environmental adaptability in confined, tortuous spaces, yet their inherent low stiffness and load capacity limit performance in precise positioning and stable support tasks. To solve the “soft...
Color image segmentation divides the image into areas that represent different objects and focus points. One of the biggest problems in color image segmentation is the lack of homogeneity in the color of real urban images, which generates areas of ov...
Magnetic Resonance Imaging (MRI) offers strong soft tissue contrast but suffers from long acquisition times and requires tedious annotation from radiologists. Traditionally, these challenges have been addressed separately with reconstruction and imag...
In this research, we propose an unsupervised method for segmentation and edge extraction of color images on the HSV space. This approach is composed of two different phases in which are applied two metaheuristic algorithms, respectively the Firefly (...
An autonomous robot that can monitor a construction site should be able to be can contextually detect its surrounding environment by recognizing objects and making decisions based on its observation. Pixel-wise semantic segmentation in real-time is v...
The large-scale identification of urban vacant land (UVL) and informal green spaces (IGSs) using conventional identification methods is challenged by the high cost of time and resources as well as inconsistent outcomes. Moreover, the spatial–te...
Aiming to implement image segmentation precisely and efficiently, we exploit new ways to encode images and achieve the optimal thresholding on quantum state space. Firstly, the state vector and density matrix are adopted for the representation of pix...
Segmentation of Agricultural Remote Sensing Images (ARSIs) stands as a pivotal component within the intelligent development path of agricultural information technology. Similarly, quick and effective delineation of urban green spaces (UGSs) in high-r...
The micro-movement feature is recognized as one of the practical features of space target recognition in academic circles. The separation of the micro-Doppler curve of the scattering center is the key to feature extraction and parameter estimation, w...
The development of the hyperspectral remote sensor technology allows the acquisition of images with a very detailed spectral information for each pixel. Because of this, hyperspectral images (HSI) potentially possess larger capabilities in solving ma...
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