About this Research Topic
The first volume of this collection comprised 10 research articles that focused on the applications of Computational Intelligence for Signal and Image Processing, such as education, healthcare, and security. The findings presented in this Research Topic showcased the active development and research within the field of Computational Intelligence methods for the times ahead.
Due to the success of that first volume and to facilitate its progression, this second volume embarks on an intriguing exploration at the intersection of neuroscience and cutting-edge technology. This edition focuses on algorithms inspired by the intricacies of the brain, delving into how these algorithms act as catalysts for the evolution of methodologies in image/video and signal processing, IoT applications, and beyond. It highlights the profound potential of brain-inspired algorithms to revolutionize various domains, paving the way for innovation and efficiency.
Moreover, this volume extends an enticing invitation to delve deeper into the reciprocal relationship between artificial intelligence and neuroscience. By showcasing the symbiotic nature of deep learning, neuro-fuzzy systems, neural networks, and other AI techniques, it emphasizes their pivotal role in deciphering and modeling the complexities of brain functions. This expansion of focus not only justifies the significance of our second volume but also opens new horizons for pioneering articles, attracting a diverse audience keen on the forefront of interdisciplinary research and innovation.
Some potential topics of interest for this Research Topic include:
• Bio-inspired Algorithms in signal, image, and video processing.
• Brain-Inspired IoT Solutions.
• Neuro-AI for Medical Diagnostics.
• Fusion of neural networks and AI in healthcare for disease prediction.
• Cognitive Computing in Robotics for decision-making.
• Brain-inspired Blockchain Solutions for Medical Image Integrity.
• Ethical Implications of Brain-inspired AI.
• Neuro-fuzzy systems and Hybrid AI Systems: Bridging Neuroscience and AI.
• Brain-Computer Interfaces and Cognitive Enhancement.
• Neural Network-based Anonymization of Medical Visual Data.
• Neural Network Interpretability and Explainability.
• Integrating Brain-Inspired Algorithms for Enhanced Medical Data Privacy.
• Brain-inspired Encryption Techniques for Medical Imaging.
• Privacy-Preserving AI for Brain Signal Analysis.
These topics aim to bridge the gap between neuroscience and technology, exploring how insights from the brain can inform the development of innovative algorithms and applications across various fields.
Due to the success of that first volume and to facilitate its progression, this second volume embarks on an intriguing exploration at the intersection of neuroscience and cutting-edge technology. This edition focuses on algorithms inspired by the intricacies of the brain, delving into how these algorithms act as catalysts for the evolution of methodologies in image/video and signal processing, IoT applications, and beyond. It highlights the profound potential of brain-inspired algorithms to revolutionize various domains, paving the way for innovation and efficiency.
Moreover, this volume extends an enticing invitation to delve deeper into the reciprocal relationship between artificial intelligence and neuroscience. By showcasing the symbiotic nature of deep learning, neuro-fuzzy systems, neural networks, and other AI techniques, it emphasizes their pivotal role in deciphering and modeling the complexities of brain functions. This expansion of focus not only justifies the significance of our second volume but also opens new horizons for pioneering articles, attracting a diverse audience keen on the forefront of interdisciplinary research and innovation.
Some potential topics of interest for this Research Topic include:
• Bio-inspired Algorithms in signal, image, and video processing.
• Brain-Inspired IoT Solutions.
• Neuro-AI for Medical Diagnostics.
• Fusion of neural networks and AI in healthcare for disease prediction.
• Cognitive Computing in Robotics for decision-making.
• Brain-inspired Blockchain Solutions for Medical Image Integrity.
• Ethical Implications of Brain-inspired AI.
• Neuro-fuzzy systems and Hybrid AI Systems: Bridging Neuroscience and AI.
• Brain-Computer Interfaces and Cognitive Enhancement.
• Neural Network-based Anonymization of Medical Visual Data.
• Neural Network Interpretability and Explainability.
• Integrating Brain-Inspired Algorithms for Enhanced Medical Data Privacy.
• Brain-inspired Encryption Techniques for Medical Imaging.
• Privacy-Preserving AI for Brain Signal Analysis.
These topics aim to bridge the gap between neuroscience and technology, exploring how insights from the brain can inform the development of innovative algorithms and applications across various fields.
Keywords: computational intelligence, deep learning, signal processing, image processing, big data
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
