Results 231 to 240 of about 1,005,453 (288)
Some of the next articles are maybe not open access.
A generalized frequency domain learning control design with experimental validation
IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, 2017This paper presents a generalized iterative learning control (ILC) design in the frequency domain with experimental validation. The optimal ILC learning function and robustness filter function are simultaneously optimized by solving a linear programming problem using frequency response functions.
Tong Duy Son +3 more
semanticscholar +2 more sources
Frequency Decoupled Domain-Irrelevant Feature Learning for Pan-Sharpening
IEEE Transactions on Circuits and Systems for Video TechnologyPan-sharpening aims to generate high-detail multi-spectral images (HRMS) through the fusion of panchromatic (PAN) and multi-spectral (MS) images. However, existing pan-sharpening methods often suffer from significant performance degradation when dealing ...
Jie Zhang +9 more
semanticscholar +2 more sources
Multi-scale frequency domain learning for texture classification
International Journal of Machine Learning and CyberneticsLiguang Zang, Yuan-cheng Li
semanticscholar +2 more sources
IEEE International Conference on Robotics and Automation, 2023
This paper proposes a novel real-time semantic segmentation network via frequency domain learning, called FDLNet, which revisits the segmentation task from two critical perspectives: spatial structure description and multilevel feature fusion.
Qingqing Yan +4 more
semanticscholar +1 more source
This paper proposes a novel real-time semantic segmentation network via frequency domain learning, called FDLNet, which revisits the segmentation task from two critical perspectives: spatial structure description and multilevel feature fusion.
Qingqing Yan +4 more
semanticscholar +1 more source
Learned Image Compression with Frequency Domain Loss
2021 International Conference on Information Networking (ICOIN), 2021This paper proposes an end-to-end deep image compression model with a frequency domain loss function. Unlike previous deep image compression methods, the model is computed jointly in the frequency domain. By calculating in the frequency domain, the model incorporates high-frequency components to capture detailed information in the reconstructed images ...
Soonbin Lee +3 more
openaire +1 more source
IEEE International Conference on Bioinformatics and Biomedicine, 2021
Medical image segmentation and classification tasks have become increasing accurate by employing deep neural networks. However, existing convolution neural networks models (CNNs) are challenging to achieve quite satisfactory results as medical objects ...
Yonghao Huang +4 more
semanticscholar +1 more source
Medical image segmentation and classification tasks have become increasing accurate by employing deep neural networks. However, existing convolution neural networks models (CNNs) are challenging to achieve quite satisfactory results as medical objects ...
Yonghao Huang +4 more
semanticscholar +1 more source
The Context Hierarchical Contrastive Learning for Time Series in Frequency Domain
Communications in Computer and Information Science, 2023Jian-Wei Liu, Liu Jian-Wei
exaly +2 more sources
Rethinking domain-agnostic continual learning via frequency completeness learning
Information FusionHaitao Zhang, Peng Jian, Jing Shen
exaly +2 more sources
Deep learning-assisted frequency-domain photoacoustic microscopy
Optics Letters, 2023Frequency-domain photoacoustic microscopy (FD-PAM) constitutes a powerful cost-efficient imaging method integrating intensity-modulated laser beams for the excitation of single-frequency photoacoustic waves. Nevertheless, FD-PAM provides an extremely small signal-to-noise ratio (SNR), which can be up to two orders of magnitude lower than the ...
Tserevelakis, George J. +6 more
openaire +2 more sources
Frequency Domain Learning Scheme for Massive MIMO Using Deep Neural Network
International Conference Intelligent Computing and Control Systems, 2020Massive MIMO is one of the cornerstones of 5G technology. MIMO scaled up to hundreds or even thousands of antenna terminals can result in an extensive increase in the capacity at reduced computational complexity.
I. C, S. Tamilselvan, S. V
semanticscholar +1 more source