Neural Architectures for Embodied AI and Cognition
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Introduces convolutional neural networks for image processing, covering basic components, architectures, and practical applications, including denoising and segmentation.
Explores the intricate relationship between neuroscience and machine learning, highlighting the challenges of analyzing neural data and the role of machine learning tools.
Explores neural signal processing, MRI techniques, and imaging validation, emphasizing structural and functional connectivity and clinical applications.
Explores decoding techniques for neural signals using invasive interfaces, regenerative electrodes, and intraneural electrodes to improve prosthesis control and reduce neuroma pain.
