Results 71 to 80 of about 649,643 (307)

Non-Parametric Conditional U-Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design

open access: yesMathematics, 2022
Stute presented the so-called conditional U-statistics generalizing the Nadaraya–Watson estimates of the regression function. Stute demonstrated their pointwise consistency and the asymptotic normality.
Salim Bouzebda, Inass Soukarieh
doaj   +1 more source

Tagging Complex Non-Verbal German Chunks with Conditional Random Fields [PDF]

open access: yes, 2014
We report on chunk tagging methods for German that recognize complex non-verbal phrases using structural chunk tags with Conditional Random Fields (CRFs). This state-of-the-art method for sequence classification achieves 93.5% accuracy on newspaper text.
Clematide, Simon, Roth, Luzia
core  

Discriminative word alignment with conditional random fields [PDF]

open access: yesProceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06, 2006
In this paper we present a novel approach for inducing word alignments from sentence aligned data. We use a Conditional Random Field (CRF), a discriminative model, which is estimated on a small supervised training set. The CRF is conditioned on both the source and target texts, and thus allows for the use of arbitrary and overlapping features over ...
Blunsom, P, Cohn, T
openaire   +2 more sources

Decision Fusion With Multiple Spatial Supports by Conditional Random Fields [PDF]

open access: yesIEEE Transactions on Geoscience and Remote Sensing, 2018
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 sharp region boundaries. Second,
D. Tuia, M. Volpi, G. Moser
semanticscholar   +1 more source

Programmable Dimensional Lithography with Digital Micromirror Devices for Multifunctional Microarchitectures

open access: yesAdvanced Materials Technologies, EarlyView.
This review explores recent advances in digital micromirror device (DMD)‐based lithography, focusing on its programmable light modulation, multi‐material compatibility, and dimensional patterning strategies. It highlights innovations from optical system design to materials integration and multifunctional applications, positioning DMD lithography as a ...
Yubin Lee   +5 more
wiley   +1 more source

Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields [PDF]

open access: yes, 2015
We apply stochastic average gradient (SAG) algorithms for training conditional random fields (CRFs). We describe a practical implementation that uses structure in the CRF gradient to reduce the memory requirement of this linearly-convergent stochastic ...
Ahmed, Mohamed Osama   +5 more
core  

Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains

open access: yesAdvanced Robotics Research, EarlyView.
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao   +3 more
wiley   +1 more source

Land Use Classification Using Conditional Random Fields for the Verification of Geospatial Databases [PDF]

open access: yesISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014
Geospatial land use databases contain important information with high benefit for several users, especially when they provide a detailed description on parcel level.
L. Albert, F. Rottensteiner, C. Heipke
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

open access: yesAdvanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields

open access: yesRemote Sensing, 2017
Object segmentation of remotely-sensed aerial (or very-high resolution, VHS) images and satellite (or high-resolution, HR) images, has been applied to many application domains, especially in road extraction in which the segmented objects are served as a ...
Teerapong Panboonyuen   +4 more
semanticscholar   +1 more source

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