Results 21 to 30 of about 3,973,078 (288)
Facial Expression Transfer Based on Conditional Generative Adversarial Networks
IEEE Access, 2023 With the development of computer vision and image transfer, facial expression transfer has been more and more widespread applications. But there are still some problems, such as lack of realistic expression, poor retention of facial identity features and
Yang Fan +3 more
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Feature Map Regularized CycleGAN for Domain Transfer
Mathematics, 2023 CycleGAN domain transfer architectures use cycle consistency loss mechanisms to enforce the bijectivity of highly underconstrained domain transfer mapping.
Lidija Krstanović +3 more
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Transferable Perturbations of Deep Feature Distributions
CoRR, 2020 Published as a conference paper at ICLR ...
Nathan Inkawhich +3 more
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Feature Space Transfer for Data Augmentation [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 The problem of data augmentation in feature space is considered. A new architecture, denoted the FeATure TransfEr Network (FATTEN), is proposed for the modeling of feature trajectories induced by variations of object pose. This architecture exploits a parametrization of the pose manifold in terms of pose and appearance.
Bo Liu 0043 +4 more
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Transfer Learning for Feature Dimensionality Reduction
The International Arab Journal of Information Technology, 2022 Transfer learning is a machine learning methodology by which a model developed for achieving a task is exploited for another related job. Many pre-trained image classification models trained on ImageNet are used for transfer learning. These pre-trained networks could also be used for classifying out of domain images by retraining them.
Nikhila Thribhuvan, Sudheep Elayidom
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Feature interaction: a critical review and considered forecast [PDF]
, 2003 The state of the art of the field of feature interactions in telecommunications services is reviewed, concentrating on three major research trends: software engineering approaches, formal methods, and on line techniques.
Magill, Evan +17 more
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Feature Spaces-based Transfer Learning [PDF]
Advances in Intelligent Systems Research, 2015 Transfer learning provides an approach to solve target tasks more quickly and effectively by using previouslyacquired knowledge learned from source tasks. Most of transfer learning approaches extract knowledge of source domain in the given feature space. The issue is that single perspective can‟t mine the relationship of source domain and target domain
Hua Zuo +3 more
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Exploring Diamond-Like Lattice Thermal Conductivity Crystals via Feature-Based Transfer Learning [PDF]
, 2019 Ultrahigh lattice thermal conductivity materials hold great importance since they play a critical role in the thermal management of electronic and optical devices.
Shenghong, Ju +5 more
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IEEE Access, 2020 Detecting the frequency of the pest occurrence is always a time consuming and laborious task for agriculture. This paper attempts to solve the problem through the combination of deep learning and pest detection.
Yuh-Shyan Chen +2 more
doaj +1 more source