Embodied AI typically combines sensors with machine learning to respond to real-world data. Examples include autonomous ...

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This time of the year, the holidays can be quite serene. Gifts are bought and (possibly) wrapped, the meal prep is locked in, and you’ve bought holiday-spice plug-in air fresheners for every ...

Deep learning, a leading technology in artificial intelligence, excels particularly in tasks involving image recognition and classification (Khasim et al., 2024). Convolutional Neural Network, as an ...

Text-to-image generative models have transformed how AI interprets textual inputs to produce compelling visual outputs. These models are used across industries for applications like content creation, ...

Please note that these are just the code examples accompanying the book, which we uploaded for your convenience; be aware that these notebooks may not be useful without the formulae and descriptive ...

The University Grants Commission (UGC) has approved draft guidelines for implementing Recognition of Prior Learning (RPL). In its meeting on November 14, 2024, the commission approved the ...

Machine learning (ML ... 101A device was used to acquire 3‐dimensional (3D) CT scan images in the DICOM (digital imaging and communications in medicine) format as the raw data for deep learning. The ...

The role of artificial intelligence (AI) and machine learning (ML) has become highly significant in cybersecurity matters. They show promising potential, but what can they actually offer us to ...