Results 11 to 20 of about 5,604,038 (200)

Domain-Augmented Domain Adaptation

open access: yesCoRR, 2022
Unsupervised domain adaptation (UDA) enables knowledge transfer from the labelled source domain to the unlabeled target domain by reducing the cross-domain discrepancy. However, most of the studies were based on direct adaptation from the source domain to the target domain and have suffered from large domain discrepancies.
Qiuhao Zeng, Tianze Luo, Boyu Wang 0004
openaire   +2 more sources

Domain Intersection and Domain Difference [PDF]

open access: yes2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019
We present a method for recovering the shared content between two visual domains as well as the content that is unique to each domain. This allows us to map from one domain to the other, in a way in which the content that is specific for the first domain is removed and the content that is specific for the second is imported from any image in the second
Sagie Benaim   +3 more
openaire   +3 more sources

Holder Domains and Poincare Domains [PDF]

open access: yesTransactions of the American Mathematical Society, 1990
A domain D ⊂
Wayne Smith, David A. Stegenga
openaire   +1 more source

Modular domain-to-domain translation network [PDF]

open access: yesNeural Computing and Applications, 2018
Domain-to-domain translation methods map images from a source domain to corresponding images from a target domain. The two domains contain images from the same classes, but these images look different. Recent approaches use generative adversarial networks in various configurations and architectures to perform the translation.
Karatsiolis, Savvas   +5 more
openaire   +5 more sources

Understanding the role of domain–domain linkers in the spatial orientation of domains in multi-domain proteins [PDF]

open access: yesJournal of Biomolecular Structure and Dynamics, 2013
Inter-domain linkers (IDLs)’ bridge flanking domains and support inter-domain communication in multi-domain proteins. Their sequence and conformational preferences enable them to carry out varied functions. They also provide sufficient flexibility to facilitate domain motions and, in conjunction with the interacting interfaces, they also regulate the ...
Bhaskara, Ramachandra M   +2 more
openaire   +3 more sources

Domain Conditional Predictors for Domain Adaptation

open access: yesCoRR, 2021
Learning guarantees often rely on assumptions of i.i.d. data, which will likely be violated in practice once predictors are deployed to perform real-world tasks. Domain adaptation approaches thus appeared as a useful framework yielding extra flexibility in that distinct train and test data distributions are supported, provided that other assumptions ...
João Monteiro   +4 more
openaire   +3 more sources

Maritime Domain Protections Research Group (archived) [PDF]

open access: yes, 2013
The Maritime Domain Protection Research Group (formerly known as the Maritime Domain Protection Task Force) was formed to investigate issues surrounding protection of the United States, its vessels, and citizens from terrorist threats originating in the ...

core   +2 more sources

Public Domain

open access: yes, 2021
Learning Objectives: Describe the public domain’s scope and relationship with copyright; Recognize the three categories of works in the public domain; Identify public domain works; Contribute your own works to the public ...
McNally, Michael B., Wakaruk, Amanda
core   +1 more source

Interconversion of multiferroic domains and domain walls [PDF]

open access: yesNature Communications, 2021
AbstractSystems with long-range order like ferromagnetism or ferroelectricity exhibit uniform, yet differently oriented three-dimensional regions called domains that are separated by two-dimensional topological defects termed domain walls. A change of the ordered state across a domain wall can lead to local non-bulk physical properties such as enhanced
E. Hassanpour   +10 more
openaire   +6 more sources

Domain-PFP Data.zip

open access: yes, 2023
Data associated with Domain-PFP: Protein Function Prediction Using Function-Aware Domain Embedding Representations.
Yuki Kagaya (17140359)   +2 more
core   +1 more source

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