It is difficult to detect ports in polarimetric SAR images due to the complicated components, morphology, and coastal environment. This paper proposes an unsupervised port detection method by extracting the water of the port based on three-component...
Retinal vessels identification and localization aim to separate the different retinal vasculature structure tissues, either wide or narrow ones, from the fundus image background and other retinal anatomical structures such as optic disc, macula, and...
Different land parcels possess unique microclimates, soils, and biological conditions, which in turn significantly influence the land parcels themselves, impacting biodiversity, hydrological relationships, land degradation, geological disasters, and...
In order to realize the unsupervised segmentation of subtle defect images on the surface of small magnetic rings and improve the segmentation accuracy and computational efficiency, here, an adaptive threshold segmentation method is proposed based on...
The accurate segmentation of retinal vascular is of great significance for the diagnosis of diseases such as diabetes, hypertension, microaneurysms and arteriosclerosis. In order to segment more deep and small blood vessels and provide more informati...
Accurate cloud segmentation is critical for astronomical observations and solar forecasting. However, traditional threshold- and texture-based methods suffer from limited accuracy (65–80%) under complex conditions such as thin cirrus or twiligh...
Speech-based depression screening is a promising non-invasive approach, but short spontaneous-speech segments often contain weak acoustic cues, fragmented semantic context, and overlapping representations between depressed and non-depressed participa...
An object-based method is proposed in this paper for change detection in urban areas with multi-sensor multispectral (MS) images. The co-registered bi-temporal images are resampled to match each other. By mapping the segmentation of one image to the...
Infrared small target detection, especially under low SCR conditions and complex backgrounds, is still a challenging research task. Considering the scale change caused by small targets rapidly moving, in this paper, a nonparametric regression-based m...
Unsupervised flood detection in large areas using Synthetic Aperture Radar (SAR) data always faces the challenge of automatic thresholding, because the histograms of large-scale images are unimodal, which thus makes it difficult to determine the thre...
The convolutional neural network (CNN) has been widely applied in medical image segmentation due to its outstanding nonlinear expression ability. However, applications of CNN are often limited by the receptive field, preventing it from modeling globa...
The specific surface area is an important parameter to characterize pore structure and adsorption properties, however, it is difficult to calculate accurately in shale rock due to its multiscale pore structure. In this paper, the representative 3D gr...
Accurate segmentation of colorectal polyps is crucial for the early screening and clinical diagnosis of colorectal cancer. However, the diverse morphology of polyps, significant variations in scale, and unstable quality of endoscopic imaging pose ser...
When using image processing technology to analyze mineral particle size in complex scenes, it is difficult to separate the objects from the background with traditional algorithms. This paper proposes an ore image segmentation algorithm based on a his...
Perception in trellised orchards is often challenged by dense canopy occlusion and overhead plastic coverings, which cause pronounced variations in sky visibility at row terminals. Accurately recognizing row terminals, including both row head and row...
Instance segmentation for high-resolution remote sensing images (HRSIs) is a fundamental yet challenging task in earth observation, which aims at achieving instance-level location and pixel-level classification for instances of interest on the earth&...
The precise extraction of field roads in hilly and terrace farmlands poses great challenges for remote sensing analysis. Farm roads are narrow and irregular, with spectra close to crop ridges, and frequently covered by tree and building shadows. Trad...
In this article, a novel approach for land cover change detection (LCCD) using very high resolution (VHR) remote sensing images based on spatial–spectral feature fusion and multi-scale segmentation voting decision is proposed. Unlike other trad...
Roads are important mode of transportation, which are very convenient for people’s daily work and life. However, it is challenging to accuratly extract road information from a high-resolution remote sensing image. This paper presents a road extractio...
Malware analytics suffer from scarce, delayed, and privacy-constrained labels, limiting fully supervised detection and hampering responsiveness to zero-day threats. We propose SMAD, a Semi-supervised Android Malicious App Detector that integrates a s...
Very high spatial resolution (VHR) satellite images possess several advantages in terms of describing the details of ground targets. Extracting built-up areas from VHR images has received increasing attention in practical applications, such as land u...
Polypropylene fibers provide an innovative solution for enhancing the crack resistance of tunnel lining segments. However, existing macro-models obscure the distinct effects of fibers on the mortar and ITZ, while explicit meso-modeling remains comput...
Coherent change detection is a technology that utilizes phase information in complex-valued synthetic aperture radar images. It is mostly used to detect subtle changes that cannot be detected by amplitude images on the ground, and it also has excelle...
Soil whitening in cold-region rice seedbeds is visually associated with surface drying and moisture variation. The timely and objective monitoring of soil surface conditions is therefore important for seedbed management. In response to the inefficien...
It is very significant for rural planning to accurately count the number and area of rural homesteads by means of automation. The development of deep learning makes it possible to achieve this goal. At present, many effective works have been conducte...
Automatic ship detection by Unmanned Airborne Vehicles (UAVs) and satellites is one of the fundamental challenges in maritime research due to the variable appearances of ships and complex sea backgrounds. To address this issue, in this paper, a novel...
The identification of wear rubber balls in the rubber ball cleaning system in heat exchange equipment directly affects the descaling efficiency. For the problem that the rubber ball image contains impurities and bubbles and the segmentation is low in...
Fire detection remains a challenging task due to varying fire scales, occlusions, and complex environmental conditions. This paper proposes the CN2VF-Net model, a novel hybrid architecture that combines vision Transformers (ViTs) and convolutional ne...
Precise segmentation of cell nuclei in pathological images is the foundation of cancer diagnosis and quantitative analysis, but blurred boundaries, scale variability, and staining differences have long constrained its reliability. To address this, th...
Wavelet-based Contourlet transform (WBCT) is a typical Multi-scale Geometric Analysis (MGA) method, it is a powerful technique to suppress background and enhance the edge of target. However, in the small target detection with the complex background,...
In order to solve the problems of low efficiency and accuracy in the traditional detection of tunnel cracks, this paper proposes a tunnel crack detection method based on a UAV (unmanned aerial vehicle) equipped with a high-speed camera and a crack re...
The accurate and efficient extraction of individual tree phenotypic traits for seabuckthorn (Hippophae rhamnoides L.) in natural forests is crucial for germplasm exploration, precision silviculture, and ecological restoration. This study extracted st...
Accurate identification of the degradation stage is key to the prediction of the remaining useful life (RUL) of bearings. The 3σ method is commonly used to identify the degradation point. However, the recognition accuracy is seriously disturbed...
In response to degraded parking slot markings caused by wear and tear, water accumulation, or occlusion, which significantly impair the perception accuracy and localization robustness of automated parking systems, this paper proposes SlotNet, a light...
Accurate delineation of rural settlements at large spatial extents is fundamental to territorial spatial governance, rural revitalization, and the improvement of human living environments. However, in medium-resolution remote sensing imagery, rural s...
This paper proposes an adaptive multi-threshold image segmentation method named IBKA-OTSU to address the limitations of existing deep learning-based image segmentation methods, particularly their heavy reliance on large-scale annotated datasets and h...
Blueberry fruit phenotypes are crucial agronomic trait indicators in blueberry breeding, and the number of fruits within the cluster, maturity, and compactness are important for evaluating blueberry harvesting methods and yield. However, the existing...
Metallic blocks and components are indispensable across the aerospace, energy, and heavy-engineering industries, where undetected internal flaws such as cracks, voids, and inclusions may precipitate catastrophic structural failure. Reliable nondestru...
Traditional manual horizon picking is time-consuming and laborious, while automatic picking methods often suffer from the limited scope of their applications and the discontinuity of picked results. In this paper, we propose a novel method for automa...
Online detection of impurities content in the corn deep-bed drying process is the key technology to ensure stable operation and to provide data support for self-adapting control of drying equipment. In this study, an automatic approach to corn image...
Blood vessels of the brain provide the human brain with the required nutrients and oxygen. As a vulnerable part of the cerebral blood supply, pathology of small vessels can cause serious problems such as Cerebral Small Vessel Diseases (CSVD). It has...
Photovoltaic power stations and impervious surfaces are difficult to distinguish from spectrally similar arid-region backgrounds, and their large differences in scale and spatial form further complicate joint extraction. This study proposes DBKNet, a...
X-ray CT imaging is an important three-dimensional non-destructive testing technique, which has been widely applied in various fields. However, segmenting image voxels as discrete material compositions may lose information below the voxel size. In th...
Computed tomography and magnetic resonance imaging are two powerful modalities which can be used in the clinical setting to produce data for the creation of patient-specific finite element analysis (FEA) models and physical analogues—for instan...
The human visual system (HVS) mechanism has been successfully introduced into the field of infrared small target detection. However, most of the current detection algorithms based on the mechanism of the human visual system ignore the continuous dire...
The safety and reliability of modern power systems are increasingly challenged by adverse environmental conditions. (1) Background: Ice accumulation on power transmission lines is recognized as a severe threat to grid stability, as tower collapse, co...
Plant surface electrical signals are key representations for non-destructive monitoring of changes in cell membrane potential, enabling real-time reflection of physiological responses and regulatory processes under external stimuli. However, the low-...
As a new type of jamming, the interrupted sampling repeater jamming (ISRJ) derived from the digital radio frequency memory (DRFM) technology, can generate coherent multiple false targets after pulse compression. At present, the traditional interferen...
Cloud masking is of central importance to the Earth Observation community. This paper deals with the problem of detecting clouds in visible and multispectral imagery from high-resolution satellite cameras. Recently, Machine Learning has offered promi...
Image segmentation is a crucial step in image processing and analysis, with multi-level thresholding being one of the important techniques for image segmentation. Existing approaches predominantly rely on metaheuristic optimization algorithms, which...
of 3