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imageanalysis, etc ; hyperspectral imagery; spatial data; Show all 3 Subjects
Abstract:
... Attention mechanisms are recently deployed in deep learning models for hyperspectral image (HSI) classification. Conventional spectral attentions typically use global pooling to aggregate spatial information, without sufficiently considering the spatial dependencies of the central pixel to be classified and its neighbours. Moreover, the limited training samples with high-dimensional spectral infor ...
imageanalysis, etc ; algorithms; land cover; landscapes; Show all 4 Subjects
Abstract:
... For multi-temporal high resolution remote sensing images, the image registration is important but difficult due to the high resolution and low-stability land-cover. Especially, the changing of land-cover, solar altitude angle, radiation intensity, and terrain fluctuation distortion in the overlapping areas can represent different image characteristics. These time-varying properties cause tradition ...
... Morphological processing has found several applications in image analysis and pattern recognition. Some of these techniques, known as morphological reconstruction algorithms, have been employed for land cover classification in remote sensing data. In this paper, we analyse the mathematical foundations, applications, and limitations of reconstruction by dilation and by erosion oriented to urban ext ...
imageanalysis, etc ; polarimetry; synthetic aperture radar; Show all 3 Subjects
Abstract:
... A feature space projection based on the nearest polarimetric and spatial neighbours is proposed for polarimetric synthetic aperture radar (PolSAR) images. The objective function is designed such that increases the class discrimination while preserves the contextual properties. Each polarimetric or spatial neighbour is contributed proportional to with its Wishart distance to the given pixel. A guid ...
imageanalysis, etc ; annealing; nanowires; transmission electron microscopy; Show all 4 Subjects
Abstract:
... Cognizing the structural characteristics of a heterointerface is significant to understand the growth mechanism of heterostructured nanowires. Here, the structural characteristics of a heterointerface in GaAs-GaAsSb heterostructured nanowires were investigated by employing spherical aberration (CS)-corrected transmission electron microscopy (TEM). It is found that some unusual dislocations are for ...
imageanalysis, etc ; automation; data collection; microstructure; titanium; Show all 5 Subjects
Abstract:
... The ability to measure elongated structures such as platelets and colonies, is an important step in the microstructural analysis of many materials. Widely used techniques and standards require extensive manual interaction making them slow, laborious, difficult to repeat and prone to human error. Automated approaches have been proposed but often fail when analysing complex microstructures. This pap ...
imageanalysis, etc ; dogs; histology; mast cells; morphometry; Show all 5 Subjects
Abstract:
... Quantitative morphologic parameters assessed in cytologic samples of canine cutaneous mast cell tumors (ccMCTs) may assist with surgical planning and prognostication. Robust cutoffs can be defined, with high reproducibility, for parameters such as the nuclear area (NA). The NA may be determined by morphometry (image analysis, NAI) or by stereology, such as the 2D-nucleator method (NAN); stereologi ...
imageanalysis, etc ; humans; models; presses; pressing; relapse; Show all 6 Subjects
Abstract:
... Laboratory models of relapse provide methods for evaluating challenges to behavioral treatments with differential reinforcement of an alternative response (DRA). Resurgence occurs with the worsening of conditions of reinforcement for appropriate behavior and renewal occurs when transitioning out of a treatment context. Across five experiments, participants recruited via online crowdsourcing presse ...
imageanalysis, etc ; microstructure; sampling; scanning electron microscopy; Show all 4 Subjects
Abstract:
... Sample thickness is an important parameter in transmission electron microscopy (TEM) imaging for interpreting image contrast and understanding the relationship between properties and microstructure. In this study, we introduce a method for sample thickness determination in scanning TEM (STEM) mode based on scanning moiré fringes (SMFs). Focal-series SMF imaging is used and sample thickness can be ...
imageanalysis, etc ; algorithms; data collection; infrastructure; Spain; Show all 5 Subjects
Abstract:
... With the proliferation of unmanned aerial vehicles (UAVs) in different contexts and application areas, efforts are being made to endow these devices with enough intelligence so as to allow them to perform complex tasks with full autonomy. In particular, covering scenarios such as disaster areas may become particularly difficult due to infrastructure shortage in some areas, often impeding a cloud-b ...
imageanalysis, etc ; remote sensing; synthetic aperture radar; Show all 3 Subjects
Abstract:
... Deep learning has been used in inverse synthetic aperture radar (ISAR) imaging to improve resolution performance, but there still exist some problems: the loss of weak scattering points, over-smoothed imaging results, and the universality and generalization. To address these problems, an ISAR resolution enhancement method of exploiting a generative adversarial network (GAN) is proposed in this pap ...
imageanalysis, etc ; data collection; models; spatial data; Show all 4 Subjects
Abstract:
... Convolutional neural networks show excellent performance in image segmentation. However, compared with natural images, remote sensing images are characterized by large coverage, multi-scale nesting, and complex geographic context. Therefore, it has been a challenging task to extract the building footprint from high-resolution remote sensing images. In this study, an end-to-end Multi-Scale Geoscien ...
imageanalysis, etc ; detection; detectors; remote sensing; sampling; Show all 5 Subjects
Abstract:
... Oriented object detection is a fundamental and challenging task in remote sensing image analysis that has recently drawn much attention. Currently, mainstream oriented object detectors are based on densely placed predefined anchors. However, the high number of anchors aggravates the positive and negative sample imbalance problem, which may lead to duplicate detections or missed detections. To addr ...
imageanalysis, etc ; models; polarimetry; synthetic aperture radar; Show all 4 Subjects
Abstract:
... The traditional fully connected convolutional conditional random field has a proven robust performance in post-processing semantic segmentation of SAR images. However, the current challenge is how to improve the richness of image features, thereby improving the accuracy of image segmentation. This paper proposes a polarization SAR image semantic segmentation method based on a dual-channel multi-si ...
imageanalysis, etc ; COVID-19 infection; liver neoplasms; lungs; Show all 4 Subjects
Abstract:
... Automatic medical image segmentation plays an important role as a diagnostic aid in the identification of diseases and their treatment in clinical settings. Recently proposed methods based on Convolutional Neural Networks (CNNs) have demonstrated their potential in image processing tasks, including some medical image analysis tasks. Those methods can learn various feature representations with nume ...
imageanalysis, etc ; algorithms; color; models; transmittance; visual perception; Show all 6 Subjects
Abstract:
... To solve the problem that traditional dark channel is not suitable for a large sky area and can easyily distort defogged images, we propose a novel fusion-based defogging algorithm. Firstly, an improved remote sensing image segmentation algorithm is introduced to mix the dark channel. Secondly, we establish a dark-light channel fusion model to calculate the atmospheric light map. Furthermore, in o ...
imageanalysis, etc ; algorithms; statistics; synthetic aperture radar; texture; Show all 5 Subjects
Abstract:
... As an all-weather and all-day remote sensing image data source, SAR (Synthetic Aperture Radar) images have been widely applied, and their registration accuracy has a direct impact on the downstream task effectiveness. The existing registration algorithms mainly focus on small sub-images, and there is a lack of available accurate matching methods for large-size images. This paper proposes a high-pr ...
imageanalysis, etc ; synthetic aperture radar; system optimization; texture; Show all 4 Subjects
Abstract:
... The recently proposed multi-objective clustering methods convert the segmentation problem to a multi-objective optimization problem by extracting multiple features from an image to be segmented as clustering data. However, most of these methods fail to consider the impacts of different features on segmentation results when calculating the similarity using the Euclidean distance. In this paper, fea ...
imageanalysis, etc ; computer vision; data collection; neural networks; Show all 4 Subjects
Abstract:
... Over the past few years, deep learning algorithms have held immense promise for better multi-spectral (MS) optical remote sensing image (RSI) analysis. Most of the proposed models, based on convolutional neural network (CNN) and fully convolutional network (FCN), have been applied successfully on computer vision images (CVIs). However, there is still a lack of exploration of spectra correlation in ...
imageanalysis, etc ; algorithms; geometry; glaciers; orthophotography; Alps region; Show all 6 Subjects
Abstract:
... Flow velocities were measured on the Plator rock glacier in the Central Italian Alps using a correlation image analysis algorithm on orthophotos acquired by drones between the years 2016 and 2020. The spatial patterns of surface creep were then compared to the Bulk Creep Factor (BCF) spatial variability to interpret the rock glacier dynamics as a function of material properties and geometry. The r ...