November 27, 2025
Deep Learning Meets Biological Vision: Lessons from Retinal Modelling
The remarkable success of deep convolutional neural networks in image recognition tasks has drawn attention to the parallels between artificial and biological visual systems. While modern architectures such as ResNet and Vision Transformers have pushed performance on benchmarks to near-human levels, the computational strategies employed by the biological retina remain a rich source of inspiration for the design of more efficient and robust visual processing systems.
The retina is far more than a passive light sensor. It contains multiple layers of neurons that perform sophisticated signal processing before any information reaches the brain. Photoreceptors convert light into electrical signals, but these signals are then processed by successive layers of bipolar, horizontal, amacrine, and ganglion cells, each contributing to operations such as contrast enhancement, motion detection, and adaptation to varying light levels.
Read more →November 17, 2025
European Smart City Initiatives and the Future of Urban Mobility
Urban mobility is undergoing a period of rapid transformation across Europe, driven by environmental policy, technological innovation, and changing citizen expectations. The European Commission has been at the forefront of this shift, funding large-scale demonstration projects that bring together cities, technology providers, and research institutions to develop and test integrated smart city solutions. The Smart Cities Marketplace, operated by the European Commission, serves as a central platform connecting these initiatives and facilitating knowledge exchange between participating cities.
Among the most ambitious of these efforts are the Horizon 2020 lighthouse projects, which designate selected cities as living laboratories for testing innovations in energy, transport, and digital infrastructure. Projects such as REMOURBAN, GrowSmarter, Triangulum, and SmarterTogether have collectively involved over 120 cities across Europe, deploying more than 550 demonstrations of technological and social innovation.
Read more →April 29, 2025
Balancing Accuracy and Interpretability in Fuzzy Classification Systems
Classification is one of the most fundamental tasks in machine learning, and the range of available techniques has grown enormously over the past two decades. Yet a recurring tension runs through the field: the methods that achieve the highest accuracy on benchmark datasets are often the most difficult for human experts to understand and trust. Fuzzy classification systems offer a distinctive middle ground, combining the ability to learn from data with a representational framework that preserves human interpretability.
Fuzzy set theory, originally proposed by Lotfi Zadeh in 1965, provides a mathematical language for expressing partial membership and vague boundaries. In the context of classification, this means that an input pattern need not belong entirely to one class or another; instead, it can have graded membership across multiple categories.
Read more →August 25, 2024
The Role of Granular Computing in Modern Artificial Intelligence
Artificial intelligence has made remarkable strides in recent years, yet many of the most powerful models remain opaque in their reasoning. Granular computing offers a compelling alternative perspective, one that is rooted in the way humans naturally process information through layers of abstraction and contextual grouping. The IEEE Systems, Man, and Cybernetics Society Technical Committee on Granular Computing has long championed this approach as a formal framework for building computational systems that operate at varying levels of detail.
At its core, granular computing is concerned with the construction and manipulation of information granules: collections of objects that are drawn together by similarity, proximity, or functional equivalence. These granules can take the form of fuzzy sets, rough sets, intervals, or clusters, depending on the nature of the problem and the level of precision required.
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