Results 41 to 50 of about 1,961,679 (175)
Transfer Learning for Radio Frequency Machine Learning: A Taxonomy and Survey
Sensors, 2022 Transfer learning is a pervasive technology in computer vision and natural language processing fields, yielding exponential performance improvements by leveraging prior knowledge gained from data with different distributions.
Lauren J. Wong, Alan J. Michaels
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“Transfer Talk” in Talk about Writing in Progress: Two Propositions about Transfer of Learning [PDF]
, 2019 This article tracks the emergence of the concept of “transfer talk”—a concept distinct from transfer of learning—and teases out the implications of transfer talk for theories of transfer of learning.
Bodee, Bridget +6 more
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Transfer learning of language-independent end-to-end ASR with language model fusion
, 2019 This work explores better adaptation methods to low-resource languages using an external language model (LM) under the framework of transfer learning. We first build a language-independent ASR system in a unified sequence-to-sequence (S2S) architecture ...
Baskar, Murali Karthick +4 more
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Effectiveness of learning transfer in National Dual Training System (NDTS) [PDF]
, 2011 Learning transfer is the ultimate goal of any training programme. The new Malaysian skills training is based on the dual learning principle in which trainees alternate between attending theoretical classes in the skills training institute and ...
Ahmad, Azmi
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Deep Transfer Learning for the Multilabel Classification of Chest X-ray Images
Diagnostics, 2022 Chest X-ray (CXR) is widely used to diagnose conditions affecting the chest, its contents, and its nearby structures. In this study, we used a private data set containing 1630 CXR images with disease labels; most of the images were disease-free, but the ...
Guan-Hua Huang +5 more
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Achieving Transfer from Mathematics Learning
Education Sciences, 2023 The question of transfer is a special challenge in mathematics teaching because the wide range and fragmentation of the curricula have in many cases fostered an instrumental understanding, which makes transfer difficult for the students. Although promoting a relational learning has been a huge step forward in achieving transfer, understanding usually ...
José Víctor Orón +1 more
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Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images
, 2019 Purpose: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, real-time in-vivo imaging with confocal laser microscopy has been proposed ...
Bengs, Marcel +6 more
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Deep Transfer Metric Learning [PDF]
IEEE Transactions on Image Processing, 2016 Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption does not hold in many real visual recognition applications, especially when samples are captured across different data sets. In this paper, we propose a new deep
Junlin Hu +3 more
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TRANSFER LEARNING APPROACH FOR CLASSIFICATION OF WIDELY USED SPICES
Yanbu Journal of Engineering and Science, 2022 People around the world relish variety of food that are flavourful. Spices add flavours to the food without adding any fat or calories. People have used spices for many centuries and are an integral part of our food.
Arunachalam Sundaram +3 more
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A survey on heterogeneous transfer learning
Journal of Big Data, 2017 Transfer learning has been demonstrated to be effective for many real-world applications as it exploits knowledge present in labeled training data from a source domain to enhance a model’s performance in a target domain, which has little or no labeled ...
Oscar Day, Taghi M. Khoshgoftaar
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