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

