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Found 10 papers, 4 papers with code
Interpretable modulated differentiable STFT and physics-informed balanced spectrum metric for freight train wheelset bearing cross-machine transfer fault diagnosis under speed fluctuations
Therefore, a cross-machine transfer diagnosis (pyDSN) network coupled with interpretable modulated differentiable short-time Fourier transform (STFT) and physics-informed balanced spectrum quality metric is proposed to learn domain-invariant and discriminative features under time-varying speeds.
HybridHash: Hybrid Convolutional and Self-Attention Deep Hashing for Image Retrieval
The experimental results demonstrate that the method proposed in this paper has superior performance with respect to state-of-the-art deep hashing methods.
Classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise
Blind deconvolution (BD) has been demonstrated as an efficacious approach for extracting bearing fault-specific features from vibration signals under strong background noise.
Make-A-Character: High Quality Text-to-3D Character Generation within Minutes
There is a growing demand for customized and expressive 3D characters with the emergence of AI agents and Metaverse, but creating 3D characters using traditional computer graphics tools is a complex and time-consuming task.
Harmonic enhancement using learnable comb filter for light-weight full-band speech enhancement model
With fewer feature dimensions, filter banks are often used in light-weight full-band speech enhancement models.
Personalized speech enhancement combining band-split RNN and speaker attentive module
Target speaker information can be utilized in speech enhancement (SE) models to more effectively extract the desired speech.
Spikformer: When Spiking Neural Network Meets Transformer
Spikformer (66. 3M parameters) with comparable size to SEW-ResNet-152 (60. 2M, 69. 26%) can achieve 74. 81% top1 accuracy on ImageNet using 4 time steps, which is the state-of-the-art in directly trained SNNs models.
Augmenting Proposals by the Detector Itself
Lacking enough high quality proposals for RoI box head has impeded two-stage and multi-stage object detectors for a long time, and many previous works try to solve it via improving RPN's performance or manually generating proposals from ground truth.
Target-Guided Structured Attention Network for Target-Dependent Sentiment Analysis
Second, it shows a strong advantage in determining the sentiment of a target when the context sentence contains multiple semantic segments.
Exploiting Effective Representations for Chinese Sentiment Analysis Using a Multi-Channel Convolutional Neural Network
Effective representation of a text is critical for various natural language processing tasks.
