RETRACTED ARTICLE: Classification of severe autism in fMRI using functional connectivity and conditional random forests
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-019-04346-y
Abstract: Autism spectrum disorder (ASD) is a complex, pervasive, and heterogeneous neurodevelopmental condition with varying trajectories and significant male bias. In this study, we considered functional magnetic resonance images of four sets of participants: set (1)… read more here.
Keywords: conditional random; autism; connectivity; set male ... See more keywords
Fine-Grained Opinion Mining on Chinese Car Reviews with Conditional Random Field
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Shanghai Jiaotong University (science)"
DOI: 10.1007/s12204-020-2184-1
Abstract: Nowadays, the Internet has penetrated into all aspects of people’s lives. A large number of online customer reviews have been accumulated in several product forums, which are valuable resources to be analyzed. However, these customer… read more here.
Keywords: conditional random; reviews conditional; fine; grained opinion ... See more keywords
Learning a constrained conditional random field for enhanced segmentation of fallen trees in ALS point clouds.
Sign Up to like & getrecommendations! Published in 2017 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2017.04.001
Abstract: Abstract In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline… read more here.
Keywords: conditional random; random field; field; segmentation ... See more keywords
De-identification of clinical notes via recurrent neural network and conditional random field.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of biomedical informatics"
DOI: 10.1016/j.jbi.2017.05.023
Abstract: De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science… read more here.
Keywords: conditional random; challenge; random field; recurrent neural ... See more keywords
Recognizing activities from partially observed streams using posterior regularized conditional random fields
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.05.004
Abstract: Abstract Recognizing activities from behavior data is important for comprehensively understanding human’s intents and interests. However, in most cases, the user behaviors are partially observed or recorded, which make it a big challenge to model… read more here.
Keywords: conditional random; random fields; posterior regularized; recognizing activities ... See more keywords
Sketch simplification based on conditional random field and least squares generative adversarial networks
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.07.065
Abstract: Abstract Sketch simplification is a critical part of cartoon drawing work. Some existing approaches are already capable of simplifying simple sketches, but in some cases, they are still insufficient because of method diversity of sketch… read more here.
Keywords: sketch simplification; simplification; random field; conditional random ... See more keywords
RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields
Sign Up to like & getrecommendations! Published in 2020 at "NeuroImage"
DOI: 10.1016/j.neuroimage.2020.116620
Abstract: Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease diagnosis, surgical planning, radiotherapy and chemotherapy. However, due to noise, motion, and partial volume effects, automated segmentation of lesions from… read more here.
Keywords: conditional random; segmentation; random; dense conditional ... See more keywords
Linear Chain Conditional Random Field for Operating Mode Identification and Multimode Process Monitoring
Sign Up to like & getrecommendations! Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c04005
Abstract: As a supervised machine learning algorithm, conditional random fields are mainly used for fault classification, which cannot detect new unknown faults. In addition, faulty variable location based on them has not been studied. In this… read more here.
Keywords: linear chain; random field; mode identification; conditional random ... See more keywords
Automatic Segmentation of Cervical Nuclei Based on Deep Learning and a Conditional Random Field
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2871153
Abstract: Automatic and accurate cervical nucleus segmentation is important because nuclei carry substantial diagnostic information for automatic computer-assisted cervical cancer screening and diagnosis systems. In this paper, we propose a cervical nucleus segmentation method in which… read more here.
Keywords: conditional random; information; random field; nuclei ... See more keywords
Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3061371
Abstract: The conditional random field is a suitable framework for contextual classification of two–dimensional (images) and three–dimensional (point clouds) data. This framework is based on probabilistic graphical models, an alternative representation of a conditional probability distribution… read more here.
Keywords: random field; structure; point; conditional random ... See more keywords
Decision Fusion With Multiple Spatial Supports by Conditional Random Fields
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2018.2797316
Abstract: Classification of remotely sensed images into land cover or land use is highly dependent on geographical information at least at two levels. First, land cover classes are observed in a spatially smooth domain separated by… read more here.
Keywords: conditional random; random fields; spatial supports; decision fusion ... See more keywords