Search Results for author:
Found 14 papers, 0 papers with code
Non-invasive Diver Respiration Rate Monitoring in Hyperbaric Lifeboat Environments using Short-Range Radar
Further, evidence is provided that the radar-based approach yields a more accurate measure of respiration rate than an audio signal from a headset microphone.
On Models and Approaches for Human Vital Signs Extraction from Short Range Radar Signals
The paper centres on an assessment of the modelling approaches for the processing of signals in CW and FMCW radar-based systems for the detection of vital signs.
Interference Motion Removal for Doppler Radar Vital Sign Detection Using Variational Encoder-Decoder Neural Network
A novel approach to the removal of interference through the use of a probabilistic deep learning model is presented.
On Input Formats for Radar Micro-Doppler Signature Processing by Convolutional Neural Networks
Convolutional neural networks have often been proposed for processing radar Micro-Doppler signatures, most commonly with the goal of classifying the signals.
A Novel Micro-Doppler Coherence Loss for Deep Learning Radar Applications
Deep learning techniques are subject to increasing adoption for a wide range of micro-Doppler applications, where predictions need to be made based on time-frequency signal representations.
Robustness of Deep Neural Networks for Micro-Doppler Radar Classification
Both small temporal shifts and adversarial examples are a result of a model overfitting on features that do not generalize well.
Major TOM: Expandable Datasets for Earth Observation
If ever larger datasets are to be built, and duplication of effort minimised, then a shared framework that allows users to combine and access multiple datasets is needed.
Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection
The advancements in the state of the art of generative Artificial Intelligence (AI) brought by diffusion models can be highly beneficial in novel contexts involving Earth observation data.
Exploring the Capability of Text-to-Image Diffusion Models with Structural Edge Guidance for Multi-Spectral Satellite Image Inpainting
The letter investigates the utility of text-to-image inpainting models for satellite image data.
IceCloudNet: Cirrus and mixed-phase cloud prediction from SEVIRI input learned from sparse supervision
Clouds containing ice particles play a crucial role in the climate system.
From LAION-5B to LAION-EO: Filtering Billions of Images Using Anchor Datasets for Satellite Image Extraction
Large datasets, such as LAION-5B, contain a diverse distribution of images shared online.
Detecting Cloud Presence in Satellite Images Using the RGB-based CLIP Vision-Language Model
This work explores capabilities of the pre-trained CLIP vision-language model to identify satellite images affected by clouds.
Neural Weight Step Video Compression
A variety of compression methods based on encoding images as weights of a neural network have been recently proposed.
Neural Knitworks: Patched Neural Implicit Representation Networks
Coordinate-based Multilayer Perceptron (MLP) networks, despite being capable of learning neural implicit representations, are not performant for internal image synthesis applications.
