Multilingual models can improve language processing, particularly for low resource
situations, by sharing parameters across languages. Multilingual acoustic models, however …

Deep learning is quickly becoming a standard approach to solving a range of materials
science objectives, particularly in the field of computer vision. However, labeled datasets …

The visual quality of ultrasound (US) images is crucial for clinical diagnosis and treatment.
The main source of image quality degradation is the inherent speckle noise generated …

High spatiotemporal resolution land surface temperature (LST) data are essential for
dynamic monitoring and prediction in climate change research. Due to the limitations of …

The metaverse, along with its various Web 3.0 sub-domains, represents a ground-breaking
extension of the physical and digital worlds. In this emerging landscape, real and virtual …

We propose an approach of graph convolutional networks for robust infant cry classification.
We construct non-fully connected graphs with weighted edges based on the similarities …

The emergence of commercial electron backscatter diffraction (EBSD) equipment ushered in
an era of information rich maps produced by determining the orientation of user-selected …

There is growing interest in building phone recognition systems for low-resource languages
as the majority of languages do not have any writing systems. Phone recognition systems …

Centered Kernel Alignment (CKA) was recently proposed as a similarity metric for
comparing activation patterns in deep networks. Here we experiment with the modified RV …

Recent automatic speech recognition (ASR) is commonly developed using deep learning
(DL), instead of the Hidden Markov Model (HMM). Many researchers show that DL is much …