Understanding how different areas of the human brain communicate with each other is a
crucial issue in neuroscience. The concepts of structural, functional and effective …

Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

Multimodal Large Language Models (MLLMs) have gained significant attention recently,
showing remarkable potential in artificial general intelligence. However, assessing the utility …

Trapped by time-consuming traditional trial-and-error methods and vast untapped
composition space, efficiently discovering novel high entropy alloys (HEAs) with exceptional …

Land cover and climate monitoring is a crucial task in agriculture, forestry, hazard
management, and ecosystems assessment. In this paper, normalized difference vegetation …

Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …

Since their inception in the 1930–1960s, the research disciplines of computational imaging
and machine learning have followed parallel tracks and, during the last two decades …

Feature selection is one of the most efficient procedures for reducing the dimensionality of
high-dimensional data by choosing a practical subset of features. Since labeled samples are …

Drug discovery is a cost and time-intensive process that is often assisted by computational
methods, such as virtual screening, to speed up and guide the design of new compounds …

Correlation in the broadest sense is a measure of an association between variables. In
correlated data, the change in the magnitude of 1 variable is associated with a change in the …