Knowledge tracing: A survey
Humans' ability to transfer knowledge through teaching is one of the essential aspects for
human intelligence. A human teacher can track the knowledge of students to customize the …
human intelligence. A human teacher can track the knowledge of students to customize the …
Toward an AI Era: advances in electronic skins
Electronic skins (e-skins) have seen intense research and rapid development in the past two
decades. To mimic the capabilities of human skin, a multitude of flexible/stretchable sensors …
decades. To mimic the capabilities of human skin, a multitude of flexible/stretchable sensors …
A CNN-RNN framework for crop yield prediction
Crop yield prediction is extremely challenging due to its dependence on multiple factors
such as crop genotype, environmental factors, management practices, and their interactions …
such as crop genotype, environmental factors, management practices, and their interactions …
Fusing physics-based and deep learning models for prognostics
Physics-based and data-driven models for remaining useful lifetime (RUL) prediction
typically suffer from two major challenges that limit their applicability to complex real-world …
typically suffer from two major challenges that limit their applicability to complex real-world …
Machine learned features from density of states for accurate adsorption energy prediction
Materials databases generated by high-throughput computational screening, typically using
density functional theory (DFT), have become valuable resources for discovering new …
density functional theory (DFT), have become valuable resources for discovering new …
Fbnetgen: Task-aware gnn-based fmri analysis via functional brain network generation
Functional magnetic resonance imaging (fMRI) is one of the most common imaging
modalities to investigate brain functions. Recent studies in neuroscience stress the great …
modalities to investigate brain functions. Recent studies in neuroscience stress the great …
State-of-the-art in 1d convolutional neural networks: A survey
Deep learning architectures have brought about new heights in computer vision, with the
most common approach being the Convolutional Neural Network (CNN). Through CNN …
most common approach being the Convolutional Neural Network (CNN). Through CNN …
Convolutional neural network in medical image analysis: a review
Medical image analysis helps in resolving clinical issues by examining clinically generated
images. In today's world of deep learning (DL) along with advances in computer vision, the …
images. In today's world of deep learning (DL) along with advances in computer vision, the …
Password-Stealing without Hacking: Wi-Fi Enabled Practical Keystroke Eavesdrop**
The contact-free sensing nature of Wi-Fi has been leveraged to achieve privacy breaches,
yet existing attacks relying on Wi-Fi CSI (channel state information) demand hacking Wi-Fi …
yet existing attacks relying on Wi-Fi CSI (channel state information) demand hacking Wi-Fi …
[HTML][HTML] Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: cough …
The issue in respiratory sound classification has attained good attention from the clinical
scientists and medical researcher's group in the last year to diagnosing COVID-19 disease …
scientists and medical researcher's group in the last year to diagnosing COVID-19 disease …