Results 1 to 10 of about 3,973,078 (288)

Semi-Supervised Instance-Segmentation Model for Feature Transfer Based on Category Attention [PDF]

Sensors, 2022
In the task of image instance segmentation, semi-supervised instance segmentation algorithms have received constant research attention over recent years.
Hao Wang, Juncai Liu, Changhai Huang, Xuewen Yang, Dasha Hu, Liangyin Chen, Xiaoqing Xing, Yuming Jiang   +7 more
doaj   +2 more sources

Attention and feature transfer based knowledge distillation [PDF]

Scientific Reports, 2023
Existing knowledge distillation (KD) methods are mainly based on features, logic, or attention, where features and logic represent the results of reasoning at different stages of a convolutional neural network, and attention maps symbolize the reasoning ...
Guoliang Yang, Shuaiying Yu, Yangyang Sheng, Hao Yang   +3 more
doaj   +2 more sources

Attention-based speech feature transfer between speakers [PDF]

Frontiers in Artificial Intelligence
In this study, we propose a simple yet effective method for incorporating the source speaker's characteristics in the target speaker's speech. This allows our model to generate the speech of the target speaker with the style of the source speaker.
Hangbok Lee, Minjae Cho, Hyuk-Yoon Kwon
doaj   +2 more sources

Joint Feature-Space and Sample-Space Based Heterogeneous Feature Transfer Method for Object Recognition Using Remote Sensing Images with Different Spatial Resolutions [PDF]

Sensors, 2021
To improve the classification results of high-resolution remote sensing images (RSIs), it is necessary to use feature transfer methods to mine the relevant information between high-resolution RSIs and low-resolution RSIs to train the classifiers together.
Wei Hu, Xiyuan Kong, Liang Xie, Huijiong Yan, Wei Qin, Xiangyi Meng, Ye Yan, Erwei Yin   +7 more
doaj   +2 more sources

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   +3 more sources

The Transmission of Substrate Features

Journal of Modern Languages, 2020
Theories of the formation of creole syntax have been proposed to explain whether substrates and superstrates influence the resultant creole structures, and if so, what the mechanisms are by which they influence them.
Robert Laub
doaj   +14 more sources

Imbalanced Fault Diagnosis of Rolling Bearing Using Data Synthesis Based on Multi-Resolution Fusion Generative Adversarial Networks

Machines, 2022
Fault diagnosis of industrial bearings plays an invaluable role in the health monitoring of rotating machinery. In practice, there is far more normal data than faulty data, so the data usually exhibit a highly skewed class distribution.
Chuanzhu Hao, Junrong Du, Haoran Liang
doaj   +1 more source

Person Re-identification Combined with Clothing Information Transfer

Jisuanji kexue yu tansuo, 2021
Person re-identification (Re-ID) is an identification method based on the overall characteristics of human body, which is usually used to judge whether there is a specific person in the image or video sequence.
YUAN Chunmiao, NIU Ying, GUO Tao, LI Xin
doaj   +1 more source

An Intelligent Fault Diagnosis Scheme Using Transferred Samples for Intershaft Bearings Under Variable Working Conditions

IEEE Access, 2020
Machine learning methods have made great development in data-driven fault diagnosis of rolling bearings. But the intelligent fault diagnosis of intershaft bearing faces the following two dilemmas: 1) the fault vibration is extremely weak, and it is ...
Ya He, Minghui Hu, Kun Feng, Zhinong Jiang   +3 more
doaj   +1 more source

Fuzzy Inference and Manifold Regularization Combined Feature Transfer Learning

Jisuanji kexue yu tansuo, 2020
Transfer learning leverages the rich data in the source domain to provide support for building accurate models in the target domain. Feature transfer learning is a kind of widely studied technology in transfer learning, but the existing feature transfer ...
SONG Yixuan, DENG Zhaohong, QIN Bin
doaj   +1 more source