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Is Grad-CAM Explainable in Medical Images?
Explainable Deep Learning has gained significant attention in the field of artificial intelligence (AI), particularly in domains such as medical imaging, where accurate and interpretable machine learning models are crucial for effective diagnosis and treatment planning.
Simulation-supervised deep learning for analysing organelles states and behaviour in living cells
Performing artificial intelligence (AI) tasks such as segmentation, tracking, and analytics of small sub-cellular structures such as mitochondria in microscopy videos of living cells is a prime example.
Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
Streaming classification methods assume the number of input features is fixed and always received.
Learning Nanoscale Motion Patterns of Vesicles in Living Cells
Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope resolution ( 250 nm), inside living biological cells is a challenging problem.
Neural network based country wise risk prediction of COVID-19
Artificial intelligence (AI) driven methods can be useful to predict the parameters, risks, and effects of such an epidemic.
