Results 31 to 40 of about 1,005,453 (288)

Joint Time-Frequency and Time Domain Learning for Speech Enhancement [PDF]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
For single-channel speech enhancement, both time-domain and time-frequency-domain methods have their respective pros and cons. In this paper, we present a cross-domain framework named TFT-Net, which takes time-frequency spectrogram as input and produces time-domain waveform as output.
Chuanxin Tang, Chong Luo 0001, Zhiyuan Zhao 0001, Wenxuan Xie, Wenjun Zeng 0001   +4 more
openaire   +1 more source

A frequency-domain approach to learning control: implementation for a robot manipulator [PDF]

IEEE Transactions on Industrial Electronics, 1992
A frequency-domain approach to the analysis and design of learning control laws for achieving a desired repetitive behavior in a dynamical system is presented. The scheme uses two separate filters in order to obtain rapid improvement in a specified bandwidth, while cutting off possibly destabilizing dynamic effects that would bar learning convergence ...
DE LUCA, Alessandro, PAESANO G, ULIVI G.
openaire   +2 more sources

A Hybrid Deep Learning Model for Air Quality Prediction Based on the Time–Frequency Domain Relationship

Atmosphere, 2023
Deep learning models have been widely used in time-series numerical prediction of atmospheric environmental quality. The fundamental feature of this application is to discover the correlation between influencing factors and target parameters through a ...
R. Xu, Deke Wang, Jian Li, H. Wan, Shiming Shen, Xin Guo   +5 more
semanticscholar   +1 more source

FDMamba: frequency-enhanced deformable Mamba for topology-aware road extraction

GIScience & Remote Sensing
Extracting topological road networks from high-resolution remote sensing imagery is a fundamental yet challenging task, often hindered by slender geometries and complex occlusions.
Zhengbo Yu, Binbin Li, Dongsheng Zhong, Zhe Chen, Weirong Yang, Zhongchang Sun, Keyan Xiao, Cheng Li, Lorenzo Picco   +8 more
doaj   +1 more source

A High-Resolution Remote Sensing Road Extraction Method Based on the Coupling of Global Spatial Features and Fourier Domain Features

Remote Sensing
Remote sensing road extraction based on deep learning is an important method for road extraction. However, in complex remote sensing images, different road information often exhibits varying frequency distributions and texture characteristics, and it is ...
Hui Yang, Caili Zhou, Xiaoyu Xing, Yongchuang Wu, Yanlan Wu   +4 more
doaj   +1 more source

Efficient Aero-Optical Degraded Image Restoration via Adaptive Frequency Selection

Remote Sensing
During high-speed flight, the aircraft causes rapid compression of the surrounding air, creating a complex turbulent flow field. This high-speed flow field interferes with the optical transmission of optical imaging systems, resulting in high-frequency ...
Yingjiao Huang, Qingpeng Zhang, Xiafei Ma, Haotong Ma   +3 more
doaj   +1 more source

A Frequency-Domain Convolutional Neural Network Architecture Based on the Frequency-Domain Randomized Offset Rectified Linear Unit and Frequency-Domain Chunk Max Pooling Method

IEEE Access, 2020
It is of great importance to construct a convolutional neural network architecture in the frequency domain to explore the theory of deep learning in the frequency domain.
Jinhua Lin, Lin Ma, Jingxia Cui
doaj   +1 more source

Frequency-domain learning-driven lightweight phase recovery method for in-line holography.

Optics Express
Retrieving phase information from a single-intensity image poses a highly ill-posed inverse problem in the field of optical imaging, particularly in applications such as in-line holography, where phase information is critical for accurate reconstruction.
Qiming An, Xiaosong Liu, Gaofu Men, Jiazhen Dou, Jianglei Di   +4 more
semanticscholar   +1 more source

PWFNet: Pyramidal Wavelet–Frequency Attention Network for Road Extraction

Remote Sensing
Road extraction from remote sensing imagery plays a critical role in applications such as autonomous driving, urban planning, and infrastructure development. Although deep learning methods have achieved notable progress, current approaches still struggle
Jinkun Zong, Yonghua Sun, Ruozeng Wang, Dinglin Xu, Xue Yang, Xiaolin Zhao   +5 more
doaj   +1 more source

Spatial-Spectral Synergy Learning in the Frequency Domain for Hyperspectral Image Super-Resolution

IEEE Access
Hyperspectral image super-resolution using deep learning has achieved remarkable results. However, most of methods are developed in the spatial domain and rarely explore solutions in the frequency domain.
Yikai Duan, Jianwen Hu, Kaixiang Xie
doaj   +1 more source