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, 2021 NOTICIAS / NEWS (“transfer”, 2018) 1) LIBROS – CAPÍTULOS DE LIBRO / BOOKS – BOOK CHAPTERS 1. Bandia, Paul F. (ed.). (2017). Orality and Translation. London: Routledge. <<www.routledge.com/Orality-and-Translation/Bandia/p/book/9781138232884>
Notícias, Transfer +2 more
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Unsupervised Local Feature Hashing for Image Similarity Search [PDF]
, 2016 The potential value of hashing techniques has led to it becoming one of the most active research areas in computer vision and multimedia. However, most existing hashing methods for image search and retrieval are based on global feature representations ...
Liu, Li, Shao, Ling, Yu, Mengyang
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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
Using Decoupled Features for Photorealistic Style Transfer
SIAM Journal on Imaging Sciences, 2023 In this work we propose a photorealistic style transfer method for image and video that is based on vision science principles and on a recent mathematical formulation for the deterministic decoupling of sample statistics. The novel aspects of our approach include matching decoupled moments of higher order than in common style transfer approaches, and ...
Trevor D. Canham +3 more
openaire +4 more sources
Refrigerant forced-convection condensation inside horizontal tubes [PDF]
, 1968 High vapor velocity condensation inside a tube was studied theoretically. The heat transfer coefficients were calculated by the momentum and heat transfer analogy.
Bae, S. +8 more
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Deep transfer network of heterogeneous domain feature in machine translation
High-Confidence Computing, 2022 In order to address the shortcoming of feature representation limitation in machine translation(MT) system, this paper presents a feature transfer method in MT.
Yupeng Liu, Yanan Zhang, Xiaochen Zhang
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Successor Features for Transfer in Reinforcement Learning
CoRR, 2016 Transfer in reinforcement learning refers to the notion that generalization should occur not only within a task but also across tasks. We propose a transfer framework for the scenario where the reward function changes between tasks but the environment's dynamics remain the same.
André Barreto 0001 +6 more
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Adolescents with high‐risk cancer face complex developmental, psychosocial, and ethical challenges that extend beyond disease‐directed treatment. Although international recommendations exist for communication, psychosocial care, pediatric palliative care, survivorship, and shared decision‐making, these have largely evolved within ...
Johanna M. C. Blom +15 more
wiley +1 more source
Transfer bounds for linear feature learning [PDF]
Machine Learning, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Allogeneic hematopoietic stem cell transplantation (alloHSCT) is an essential therapy for several malignant and nonmalignant diseases, but relapse and graft loss remain the principal threats to its success. Routine monitoring of chimerism and minimal residual disease (MRD) enables early detection of imminent recurrence and guides ...
Carmen Junk +10 more
wiley +1 more source