Results 101 to 110 of about 47,039 (298)
Remote Sensing, 2019 Classification of hyperspectral images is a challenging task owing to the high dimensionality of the data, limited ground truth data, collinearity of the spectra and the presence of mixed pixels.
Vera Andrejchenko +3 more
doaj +1 more source
Markov random field segmentation of LSFM acquisitions [PDF]
Automatic segmentation of light-sheet fluorescence microscopy acquisitions using Markov random field method.
Di Giovanna, Antonino Paolo
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Myelodysplastic Syndromes: 2026 Update on Diagnosis, Risk‐Stratification and Management
American Journal of Hematology, EarlyView.ABSTRACT Disease Overview The myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid disorders characterized by peripheral blood cytopenias and increased risk of transformation to acute myelogenous leukemia (AML). MDS occurs more frequently in older males and in individuals with prior exposure to cytotoxic therapy.
Guillermo Garcia‐Manero
wiley +1 more source
Вісник Національного технічного університету "ХПÌ": Системний аналіз, управління та інформаційні технології, 2017 A three-dimensional field with properties of stationary, normality and Markov process is considered. In the paper is considered a three-dimensional field, which has the properties of stationarity, normality, and process of Markov.
Александр Сергеевич Мазманишвили +1 more
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Hidden Markov random field models for cell-type assignment of spatially resolved transcriptomics. [PDF]
Bioinformatics, 2023 Zhong C, Tian T, Wei Z.
europepmc +1 more source
A probabilistic sparse skeleton based object detection [PDF]
, 2016 We present a Markov Random Field (MRF) based skeleton model for object shape and employ it in a probabilistic chamfer-matching framework for shape based object detection.
Tarı, Zehra Sibel +3 more
core +1 more source
Advances in causal discovery methods for ecological time series
Biological Reviews, EarlyView.ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki +6 more
wiley +1 more source
Combining Convolutional Neural Network and Markov Random Field for Semantic Image Retrieval
Advances in Multimedia, 2018 With the rapidly growing number of images over the Internet, efficient scalable semantic image retrieval becomes increasingly important. This paper presents a novel approach for semantic image retrieval by combining Convolutional Neural Network (CNN) and
Haijiao Xu +4 more
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Adaptive Gaussian Markov random field spatiotemporal models for infectious disease mapping and forecasting. [PDF]
Spat Stat, 2023 MacNab YC.
europepmc +1 more source
A spin glass model of a Markov random field [PDF]
, 2006 This paper presents a novel algorithm for robust object recognition. We propose to model the visual appearance of objects via probability density functions. The algorithm consists of a fully connected Markov random field with energy function derived from
B. Caputo, CAPUTO, BARBARA
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