Results 31 to 40 of about 2,079,458 (324)

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
doaj   +1 more source

Semantic Deep Intermodal Feature Transfer: Transferring Feature Descriptors Between Imaging Modalities

, 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
Kleinschmidt, Sebastian P., Wagner, Bernardo   +1 more
openaire   +2 more sources

Towards Understanding Transfer Learning Algorithms Using Meta Transfer Features [PDF]

, 2020
Transfer learning, which aims to reuse knowledge in different domains, has achieved great success in many scenarios via minimizing domain discrepancy and enhancing feature discriminability. However, there are seldom practical determination methods for measuring the transferability among domains.
Li, Xin-Chun, Zhan, De-Chuan, Yang, Jia-Qi, Shi, Yi, Hang, Cheng, Lu, Yi   +5 more
openaire   +1 more source

Feature-Based Transfer Learning Based on Distribution Similarity

IEEE Access, 2018
Transfer learning has been found helpful at enhancing the target domain's learning process by transferring useful knowledge from other different but related source domains.
Xiaofeng Zhong, Shize Guo, Hong Shan, Liang Gao, Di Xue, Nan Zhao   +5 more
doaj   +1 more source

Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images

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, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider, Farzad Khalvati   +5 more
doaj   +1 more source

Geodesic Flow Kernel Support Vector Machine for Hyperspectral Image Classification by Unsupervised Subspace Feature Transfer

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, Paolo Gamba, Jilili Abuduwaili, Sicong Liu, Zelang Miao   +4 more
doaj   +1 more source

A brain-like classification method for computed tomography images based on adaptive feature matching dual-source domain heterogeneous transfer learning

Frontiers in Human Neuroscience, 2022
Transfer learning can improve the robustness of deep learning in the case of small samples. However, when the semantic difference between the source domain data and the target domain data is large, transfer learning easily introduces redundant features ...
Yehang Chen, Yehang Chen, Xiangmeng Chen
doaj   +1 more source

Constrained Deep Transfer Feature Learning and its Applications

, 2017
Feature learning with deep models has achieved impressive results for both data representation and classification for various vision tasks. Deep feature learning, however, typically requires a large amount of training data, which may not be feasible for ...
Ji, Qiang, Wu, Yue
core   +1 more source

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
doaj   +1 more source

Ultraviolet Dust Grain Properties in Starburst Galaxies: Evidence from Radiative Transfer Modeling and Local Group Extinction Curves

, 2005
This paper summarizes the evidence of the ultraviolet properties of dust grains found in starburst galaxies. Observations of starburst galaxies clearly show that the 2175 A feature is weak or absent.
Gordon, Karl D.
core   +2 more sources