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Found 12 papers, 9 papers with code
GRAPPA-GANs for Parallel MRI Reconstruction
For various acceleration rates, GAN and GRAPPA reconstructions were compared in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM).
Differentially Private Synthetic Medical Data Generation using Convolutional GANs
Deep learning models have demonstrated superior performance in several application problems, such as image classification and speech processing.
On the Evaluation of Generative Adversarial Networks By Discriminative Models
Generative Adversarial Networks (GANs) can accurately model complex multi-dimensional data and generate realistic samples.
Natural Language Processing Advancements By Deep Learning: A Survey
Natural Language Processing (NLP) helps empower intelligent machines by enhancing a better understanding of the human language for linguistic-based human-computer communication.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare Records
To demonstrate the model fidelity, we show that CorGAN generates synthetic data with performance similar to that of real data in various Machine Learning settings such as classification and prediction.
Ranked #1 on
Synthetic Data Generation
on UCI Epileptic Seizure Recognition
(using extra training data)
GASL: Guided Attention for Sparsity Learning in Deep Neural Networks
The main goal of network pruning is imposing sparsity on the neural network by increasing the number of parameters with zero value in order to reduce the architecture size and the computational speedup.
Generalized Bilinear Deep Convolutional Neural Networks for Multimodal Biometric Identification
We demonstrate that, rather than spatial fusion at the convolutional layers, the fusion can be performed on the outputs of the fully-connected layers of the modality-specific CNNs without any loss of performance and with significant reduction in the number of parameters.
SpeechPy - A Library for Speech Processing and Recognition
SpeechPy is an open source Python package that contains speech preprocessing techniques, speech features, and important post-processing operations.
Sound Audio and Speech Processing
Attention-Based Guided Structured Sparsity of Deep Neural Networks
Network pruning is aimed at imposing sparsity in a neural network architecture by increasing the portion of zero-valued weights for reducing its size regarding energy-efficiency consideration and increasing evaluation speed.
3D Convolutional Neural Networks for Cross Audio-Visual Matching Recognition
We propose the use of a coupled 3D Convolutional Neural Network (3D-CNN) architecture that can map both modalities into a representation space to evaluate the correspondence of audio-visual streams using the learned multimodal features.
Text-Independent Speaker Verification Using 3D Convolutional Neural Networks
In our paper, we propose an adaptive feature learning by utilizing the 3D-CNNs for direct speaker model creation in which, for both development and enrollment phases, an identical number of spoken utterances per speaker is fed to the network for representing the speakers' utterances and creation of the speaker model.
Automatic Detection of Small Groups of Persons, Influential Members, Relations and Hierarchy in Written Conversations Using Fuzzy Logic
The classifier will be based on fuzzy logic.
