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CABIF-Net: Robust Confidence-Based Audio-Visual Fusion for Fine-Grained Bird Recognition. [PDF]
Biology (Basel)Li Z, Zhang Y, Lv D, Yu Y.
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The Effect of Modulation Enhancement Scheme on Speech Recognition in Spatial Noise Among Young Adults with Normal Hearing. [PDF]
Audiol ResKanagokar V +3 more
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A Learnable Distortion Correction Module for Modulation Recognition [PDF]
IEEE Wireless Communications Letters, 2019 Modulation recognition is a challenging task while performing spectrum sensing in a cognitive radio setup. Recently, the use of deep convolutional neural networks (CNNs) has shown to achieve state-of-the-art accuracy for modulation recognition \cite{survey}.
Kumar Yashashwi +2 more
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Modulation Recognition With Graph Convolutional Network
IEEE Wireless Communications Letters, 2020In most non-cooperative communication systems, modulation recognition is a fundamental and critical technique. Traditional methods of modulation recognition can be categorized as maximum likelihood hypothesis algorithms and pattern recognition algorithms. However, these methods have high complexities or need additional data preprocessing.
Yabo Liu, Yi Liu
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Automatic Modulation Recognition for Secondary Modulated Signals
IEEE Wireless Communications Letters, 2021Automatic modulation recognition (AMR) for secondary modulated signals, remains as a bottleneck, since both analog and digital modulation are adopted in one signal. To address this issue, we focus on the original signal spectrum and the 2nd order spectrum of the pre-demodulated signal, which imply modulation features.
Peng Chu +3 more
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Attention Pyramid Module for Scene Recognition
2020 25th International Conference on Pattern Recognition (ICPR), 2021The unrestricted open vocabulary and diverse substances of scenery images bring significant challenges to scene recognition. However, most deep learning architectures and attention methods are developed on general-purpose datasets and omit the characteristics of scene data.
Zhinan Qiao +3 more
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Automatic modulation recognition—I
Journal of the Franklin Institute, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Azzouz, E. E., Nandi, A. K.
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