RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields [PDF]
NeuroImage, 2020 Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease diagnosis, surgical planning, radiotherapy and chemotherapy.
Gaoxiang Chen +4 more
doaj +4 more sources
Brain Tumor Segmentation Using Deep Capsule Network and Latent-Dynamic Conditional Random Fields [PDF]
Journal of Imaging, 2022 Because of the large variabilities in brain tumors, automating segmentation remains a difficult task. We propose an automated method to segment brain tumors by integrating the deep capsule network (CapsNet) and the latent-dynamic condition random field ...
Mahmoud Elmezain +3 more
doaj +2 more sources
Melanoma segmentation using deep learning with test-time augmentations and conditional random fields [PDF]
Scientific Reports, 2022 In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in shape and size of the skin lesion makes the segmentation task more challenging.
Hassan Ashraf +4 more
doaj +2 more sources
Gaussian conditional random fields for classification
Expert Systems With Applications, 2023 Draft paper without experimental ...
Mladen Nikolic +2 more
exaly +4 more sources
Protein alignment based on higher order conditional random fields for template-based modeling. [PDF]
PLoS ONE, 2018 The query-template alignment of proteins is one of the most critical steps of template-based modeling methods used to predict the 3D structure of a query protein.
Juan A Morales-Cordovilla +2 more
doaj +2 more sources
SkipCor: skip-mention coreference resolution using linear-chain conditional random fields. [PDF]
PLoS ONE, 2014 Coreference resolution tries to identify all expressions (called mentions) in observed text that refer to the same entity. Beside entity extraction and relation extraction, it represents one of the three complementary tasks in Information Extraction.
Slavko Žitnik +2 more
doaj +2 more sources
Personalized Driver Gene Prediction Using Graph Convolutional Networks with Conditional Random Fields [PDF]
BiologyCancer is a complex and evolutionary disease mainly driven by the accumulation of genetic variations in genes. Identifying cancer driver genes is important. However, most related studies have focused on the population level. Cancer is a disease with high
Pi-Jing Wei +3 more
doaj +2 more sources
Conditional random fields for fast, large-scale genome-wide association studies. [PDF]
PLoS ONE, 2011 Understanding the role of genetic variation in human diseases remains an important problem to be solved in genomics. An important component of such variation consist of variations at single sites in DNA, or single nucleotide polymorphisms (SNPs ...
Jim C Huang +3 more
doaj +2 more sources
Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields [PDF]
Sensors, 2014 Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D) space. In this research, we use 3D depth information from hand motions,
Hee-Deok Yang
doaj +2 more sources
Conditional Random Fields as Recurrent Neural Networks [PDF]
2015 IEEE International Conference on Computer Vision (ICCV), 2016 Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have attempted to harness the capabilities of deep learning techniques for image recognition to tackle pixel-level labelling tasks ...
Du, Dalong +7 more
core +5 more sources