The rapid advances in artificial intelligence (AI) and machine learning have transformed computer technology. Now, computers can learn and adapt autonomously, make sound judgments, and create environments in which humans and AI work in harmony. Analy... read more
Accurate prediction of rainfall events is vital for agriculture, hydrology, flood preparedness, and climate-adaptive strategies in regions of Pakistan susceptible to monsoons and droughts. Increasing climate variability highlights the need for reliab... read more
Efficient and accurate detection of fish in turbid underwater environments is crucial for aquaculture management, biomass estimation, and ecosystem monitoring. Traditional underwater analysis methods rely on handcrafted features and classical machine... read more
We present a wavefront coding (WFC) based decoupled illumination-detection light sheet fluorescence microscopy (DID-LSFM) system that integrates machine learning for high-speed volumetric imaging. This approach enables high-speed volumetric imaging o... read more
Female reproductive aging has systemic health implications, yet tissue-level dynamics remain poorly understood. Here we integrate deep learning analysis of 1,112 histology images with RNA sequencing from 659 samples across seven female reproductive o... read more
Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity in complex biological systems. However, analyzing and integrating scRNA-seq data poses unique computational challenges due to sparsity, high variabi... read more
Ensuring the reliability of critical infrastructure systems is essential for industrial and agricultural sustainability. This study focuses on analyzing the reliability of two interconnected systems: a centrifugal pumping system, comprising an impell... read more
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