Development of Artificial Intelligence to Support Needle Electromyography Diagnostic Analysis [PDF]
Healthcare Informatics Research, 2019 ObjectivesThis study proposes a method for classifying three types of resting membrane potential signals obtained as images through diagnostic needle electromyography (EMG) using TensorFlow-Slim and Python to implement an artificial-intelligence-based ...
Sangwoo Nam +4 more
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Convolutional Neural Networks for Automatic Cognitive Radio Waveform Recognition
IEEE Access, 2017 Cognitive radio technology is an important branch in the field of wireless communication, and automatic identification is a major part of cognitive radio technology. Convolutional neural network (CNN) is an advanced neural network, which is the forefront
Ming Zhang, Ming Diao, Limin Guo
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Wavelet-based filtration procedure for denoising the predicted CO2 waveforms in smart home within the Internet of Things [PDF]
, 2020 The operating cost minimization of smart homes can be achieved with the optimization of the management of the building's technical functions by determination of the current occupancy status of the individual monitored spaces of a smart home.
Augustynek, Martin +4 more
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Extended Target Recognition in Cognitive Radar Networks
Sensors, 2010 We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized ...
Xiqin Wang +3 more
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LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion
IEEE Access, 2021 Deep neural networks are used as effective methods for the Low Probability of Intercept (LPI) radar waveform recognition. However, existing models' performance degrades seriously at low Signal-to-Noise Ratios (SNRs) because the effective features ...
Xue Ni +4 more
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Waveform considerations in space-variant optical processors [PDF]
, 1978 The use of coded waveforms in space-variant optical signal processors using coordinate transformations is considered. It is shown that nonlinear transmitted coded signals must be used with such a processor and that this results in novel waveform design ...
Casasent, David, Psaltis, Demetri
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Radar Waveform Recognition Based on Multiple Autocorrelation Images
IEEE Access, 2019 Radar signal waveform recognition, as a key component of radar target recognition, has always been a research topic of great concern in the field of electronic countermeasures. In this paper, aiming at the contradiction between improving recognition rate
Zhi Huang, Zhiyuan Ma, Gaoming Huang
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Texture recognition based on magnetostrictive tactile sensor array and convolutional neural network
AIP Advances, 2023 Tactile sensors are key devices in surface information perception for robots that can recognize the surface texture of fabrics with different materials and winding patterns in unstructured environments, thus helping the robot process fabrics more ...
Zhuolin Li +4 more
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Attention-based Wav2Text with Feature Transfer Learning
, 2017 Conventional automatic speech recognition (ASR) typically performs multi-level pattern recognition tasks that map the acoustic speech waveform into a hierarchy of speech units.
Nakamura, Satoshi +2 more
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BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis
, 2020 The ever evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction (HCI) and affective ...
Gu, Yu +3 more
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