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Found 11 papers, 2 papers with code
Contrastive Deep Encoding Enables Uncertainty-aware Machine-learning-assisted Histopathology
We show that our approach can reach the state-of-the-art (SOTA) for patch-level classification with only 1-10% randomly selected annotations compared to other SOTA approaches.
MOSAIC: Masked Optimisation with Selective Attention for Image Reconstruction
To this end, we propose MOSAIC, a novel compressive sensing framework to reconstruct images given any random selection of measurements, sampled using a fixed basis.
A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG Data
Sleep plays a crucial role in the well-being of human lives.
Vision Transformer with Convolutional Encoder-Decoder for Hand Gesture Recognition using 24 GHz Doppler Radar
Transformers combined with convolutional encoders have been recently used for hand gesture recognition (HGR) using micro-Doppler signatures.
Towards Interpretable Sleep Stage Classification Using Cross-Modal Transformers
Here, we propose a cross-modal transformer, which is a transformer-based method for sleep stage classification.
Ranked #2 on
Automatic Sleep Stage Classification
on Sleep-EDF
Automatic Sleep Stage Classification
General Classification
+3
Deep Optical Coding Design in Computational Imaging
The performance of COI systems highly depends on the design of its main components: the CE pattern and the computational method used to perform a given task.
From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopy
To this end, we present a learnable optical compression-decompression framework that learns content-specific features.
Differentiable Microscopy Designs an All Optical Phase Retrieval Microscope
Since the late 16th century, scientists have continuously innovated and developed new microscope types for various applications.
PointCaps: Raw Point Cloud Processing using Capsule Networks with Euclidean Distance Routing
We address these limitations in existing capsule network based approaches by proposing PointCaps, a novel convolutional capsule architecture with parameter sharing.
WLS Design of ARMA Graph Filters using Iterative Second-Order Cone Programming
We propose a weighted least-square (WLS) method to design autoregressive moving average (ARMA) graph filters.
A Novel Transfer Learning-Based Approach for Screening Pre-existing Heart Diseases Using Synchronized ECG Signals and Heart Sounds
Furthermore, our results show that individually collected ECG or PCG waveforms are able to provide transferable features which could effectively help to make use of a limited number of synchronized PCG and ECG waveforms and still achieve significant classification performance.
