Search Results for author:
Found 11 papers, 2 papers with code
XAI-BayesHAR: A novel Framework for Human Activity Recognition with Integrated Uncertainty and Shapely Values
Human activity recognition (HAR) using IMU sensors, namely accelerometer and gyroscope, has several applications in smart homes, healthcare and human-machine interface systems.
Explainable Artificial Intelligence (XAI)
Human Activity Recognition
+1
Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach
In this work, model explanations are fed back to the feed-forward training to help the model generalize better.
Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking
There, we show that our method outperforms related Meta-RL approaches on unseen tracking scenarios in peak performance by 16% and the baseline by 35% while detecting OOD data with an F1-Score of 72%.
MEET: A Monte Carlo Exploration-Exploitation Trade-off for Buffer Sampling
This is enabled by the uncertainty estimation of the Q-Value function, which guides the sampling to explore more significant transitions and, thus, learn a more efficient policy.
Utilizing Explainable AI for improving the Performance of Neural Networks
To address this, Explainable Artificial Intelligence (XAI) has been developing as a field that aims to improve the transparency of the model and increase their trustworthiness.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Radar Image Reconstruction from Raw ADC Data using Parametric Variational Autoencoder with Domain Adaptation
This paper presents a parametric variational autoencoder-based human target detection and localization framework working directly with the raw analog-to-digital converter data from the frequency modulated continous wave radar.
Cross-modal Learning of Graph Representations using Radar Point Cloud for Long-Range Gesture Recognition
Gesture recognition is one of the most intuitive ways of interaction and has gathered particular attention for human computer interaction.
Light-weight Gesture Sensing Using FMCW Radar Time Series Data
The paper proposes a novel feature extraction approach for FMCW radar systems in the field of short-range gesture sensing.
A Matched-filter based method in the Synthetic Aperture Radar Images Using FMCW radar
In this paper, we aim to propose a method whereby stretch processing can achieve optimal SNR.
Label-Aware Ranked Loss for robust People Counting using Automotive in-cabin Radar
In this paper, we introduce the Label-Aware Ranked loss, a novel metric loss function.
COVIDLite: A depth-wise separable deep neural network with white balance and CLAHE for detection of COVID-19
For making available an alternative diagnostic method, we proposed a deep neural network based diagnostic method which can be easily integrated with mobile devices for detection of COVID-19 and viral pneumonia using Chest X-rays (CXR) images.
