Results 31 to 40 of about 3,973,078 (288)
Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer
Sensors, 2022 For conventional near-infrared spectroscopy (NIR) technology, even within the same sample, the NIR spectral signal can vary significantly with variation of spectrometers and the spectral collection environment.
Zheyu Zhang +4 more
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CoRR, 2019 Under difficult environmental conditions, the view of RGB cameras may be restricted by fog, dust or difficult lighting situations. Because thermal cameras visualize thermal radiation, they are not subject to the same limitations as RGB cameras. However, because RGB and thermal imaging differ significantly in appearance, common, state-of-the-art feature
Sebastian P. Kleinschmidt +1 more
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Transfer Learning Oriented Text Feature Alignment Algorithm [PDF]
Jisuanji gongcheng, 2017 The inconsistency between source domain and target domain feature spaces results in accuracy decline of transfer learning.To resolve this problem,this paper proposes a different domain feature alignment method based on Word2Vec.Adjectives,adverbs,nouns ...
WEI Xiaocong,LIN Hongfei
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UNSUPERVISED TRANSUDATIVE TL FEATURE LEARNING FOR IMAGE FEATURE EXTRACTION AND REPRESENTATION [PDF]
ICTACT Journal on Image and Video Processing, 2023 In this study, we address the problem of unsupervised transductive transfer learning for image feature extraction and representation. While transfer learning has shown promising results in various domains, its application to image feature extraction in ...
Logeshwari Dhavamani +3 more
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Experimental determination of natural convection heat transfer coefficients in an attic shaped enclosure [PDF]
, 2010 Heat transfer by natural convection in triangular enclosures is an area of significant importance in applications such as the design of greenhouses, attics and solar water heaters.
Carson, James K. +2 more
core +1 more source
Transfer with Model Features in Reinforcement Learning
CoRR, 2018 A key question in Reinforcement Learning is which representation an agent can learn to efficiently reuse knowledge between different tasks. Recently the Successor Representation was shown to have empirical benefits for transferring knowledge between tasks with shared transition dynamics. This paper presents Model Features: a feature representation that
Lucas Lehnert, Michael L. Littman
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Remote Sensing, 2016 In order to deal with scenarios where the training data, used to deduce a model, and the validation data have different statistical distributions, we study the problem of transformed subspace feature transfer for domain adaptation (DA) in the context of ...
Alim Samat +4 more
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Scientific Reports, 2021 As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past decade. On the other hand, recent advances in deep learning and transfer learning have shown significant potential in the ...
Yucheng Zhang +5 more
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Attention-based Wav2Text with feature transfer learning [PDF]
2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2017 Conventional automatic speech recognition (ASR) typically performs multi-level pattern recognition tasks that map the acoustic speech waveform into a hierarchy of speech units. But, it is widely known that information loss in the earlier stage can propagate through the later stages.
Andros Tjandra +2 more
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Effective Transfer Learning with Label-Based Discriminative Feature Learning
Sensors, 2022 The performance of natural language processing with a transfer learning methodology has improved by applying pre-training language models to downstream tasks with a large number of general data.
Gyunyeop Kim, Sangwoo Kang
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