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Found 15 papers, 6 papers with code
ACC-ViT : Atrous Convolution's Comeback in Vision Transformers
At present two classes of attentions prevail in vision transformers, regional and sparse attention.
ACC-UNet: A Completely Convolutional UNet model for the 2020s
This decade is marked by the introduction of Vision Transformer, a radical paradigm shift in broad computer vision.
RamanNet: A generalized neural network architecture for Raman Spectrum Analysis
Raman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kind of materials.
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor.
Segmentation of Lung Tumor from CT Images using Deep Supervision
Lung cancer is a leading cause of death in most countries of the world.
A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals
Most existing methods used in the hospitals for continuous monitoring of BP are invasive.
Application of Sequence Embedding in Protein Sequence-Based Predictions
In sequence-based predictions, conventionally an input sequence is represented by a multiple sequence alignment (MSA) or a representation derived from MSA, such as a position-specific scoring matrix.
QUCoughScope: An Artificially Intelligent Mobile Application to Detect Asymptomatic COVID-19 Patients using Cough and Breathing Sounds
Test subjects can simply download a mobile application, enter their symptoms, record an audio clip of their cough and breath, and upload the data anonymously to our servers.
COVID-19 Infection Localization and Severity Grading from Chest X-ray Images
In this study, we address this urgent need by proposing a systematic and unified approach for lung segmentation and COVID-19 localization with infection quantification from CXR images.
EDITH :ECG biometrics aided by Deep learning for reliable Individual auTHentication
In this work, we present, EDITH, a deep learning-based framework for ECG biometrics authentication system.
Detection and severity classification of COVID-19 in CT images using deep learning
Furthermore, the proposed system achieved an elegant performance for COVID-19 infection segmentation with a DSC of 94. 13% and IoU of 91. 85% using the FPN model with the DenseNet201 encoder.
Align-gram : Rethinking the Skip-gram Model for Protein Sequence Analysis
Background: The inception of next generations sequencing technologies have exponentially increased the volume of biological sequence data.
PPG2ABP: Translating Photoplethysmogram (PPG) Signals to Arterial Blood Pressure (ABP) Waveforms using Fully Convolutional Neural Networks
This motivates us to develop a method to predict the continuous arterial blood pressure (ABP) waveform through a non-invasive approach using photoplethysmogram (PPG) signals.
MultiResUNet : Rethinking the U-Net Architecture for Multimodal Biomedical Image Segmentation
We have compared our proposed architecture MultiResUNet with the classical U-Net on a vast repertoire of multimodal medical images.
VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals
Ventricular Fibrillation (VF), one of the most dangerous arrhythmias, is responsible for sudden cardiac arrests.
