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Found 5 papers, 1 papers with code
RespireNet: A Deep Neural Network for Accurately Detecting Abnormal Lung Sounds in Limited Data Setting
Auscultation of respiratory sounds is the primary tool for screening and diagnosing lung diseases.
Ranked #10 on
Audio Classification
on ICBHI Respiratory Sound Database
(using extra training data)
Learning a Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution
Adversarially trained deep neural networks have significantly improved performance of single image super resolution, by hallucinating photorealistic local textures, thereby greatly reducing the perception difference between a real high resolution image and its super resolved (SR) counterpart.
UltraCompression: Framework for High Density Compression of Ultrasound Volumes using Physics Modeling Deep Neural Networks
Ultrasound image compression by preserving speckle-based key information is a challenging task.
End-To-End Audio Replay Attack Detection Using Deep Convolutional Networks with Attention
Our proposed approach uses a novel visual attention mechanism on time-frequency representations of utterances based on group delay features, via deep residual learning (an adaptation of ResNet-18 architecture).
Simulating Patho-realistic Ultrasound Images using Deep Generative Networks with Adversarial Learning
We also quantify the shift in tissue specific intensity distributions of the real and simulated images to prove their similarity.
