5,607 research outputs found

    Principles of generalization for sensorimotor cerebellar learning

    Get PDF

    Self-supervised learning for transferable representations

    Get PDF
    Machine learning has undeniably achieved remarkable advances thanks to large labelled datasets and supervised learning. However, this progress is constrained by the labour-intensive annotation process. It is not feasible to generate extensive labelled datasets for every problem we aim to address. Consequently, there has been a notable shift in recent times toward approaches that solely leverage raw data. Among these, self-supervised learning has emerged as a particularly powerful approach, offering scalability to massive datasets and showcasing considerable potential for effective knowledge transfer. This thesis investigates self-supervised representation learning with a strong focus on computer vision applications. We provide a comprehensive survey of self-supervised methods across various modalities, introducing a taxonomy that categorises them into four distinct families while also highlighting practical considerations for real-world implementation. Our focus thenceforth is on the computer vision modality, where we perform a comprehensive benchmark evaluation of state-of-the-art self supervised models against many diverse downstream transfer tasks. Our findings reveal that self-supervised models often outperform supervised learning across a spectrum of tasks, albeit with correlations weakening as tasks transition beyond classification, particularly for datasets with distribution shifts. Digging deeper, we investigate the influence of data augmentation on the transferability of contrastive learners, uncovering a trade-off between spatial and appearance-based invariances that generalise to real-world transformations. This begins to explain the differing empirical performances achieved by self-supervised learners on different downstream tasks, and it showcases the advantages of specialised representations produced with tailored augmentation. Finally, we introduce a novel self-supervised pre-training algorithm for object detection, aligning pre-training with downstream architecture and objectives, leading to reduced localisation errors and improved label efficiency. In conclusion, this thesis contributes a comprehensive understanding of self-supervised representation learning and its role in enabling effective transfer across computer vision tasks

    Principles of generalization for sensorimotor cerebellar learning

    Get PDF

    Multidisciplinary perspectives on Artificial Intelligence and the law

    Get PDF
    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Natural and Technological Hazards in Urban Areas

    Get PDF
    Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

    La traduzione specializzata all’opera per una piccola impresa in espansione: la mia esperienza di internazionalizzazione in cinese di Bioretics© S.r.l.

    Get PDF
    Global markets are currently immersed in two all-encompassing and unstoppable processes: internationalization and globalization. While the former pushes companies to look beyond the borders of their country of origin to forge relationships with foreign trading partners, the latter fosters the standardization in all countries, by reducing spatiotemporal distances and breaking down geographical, political, economic and socio-cultural barriers. In recent decades, another domain has appeared to propel these unifying drives: Artificial Intelligence, together with its high technologies aiming to implement human cognitive abilities in machinery. The “Language Toolkit – Le lingue straniere al servizio dell’internazionalizzazione dell’impresa” project, promoted by the Department of Interpreting and Translation (Forlì Campus) in collaboration with the Romagna Chamber of Commerce (Forlì-Cesena and Rimini), seeks to help Italian SMEs make their way into the global market. It is precisely within this project that this dissertation has been conceived. Indeed, its purpose is to present the translation and localization project from English into Chinese of a series of texts produced by Bioretics© S.r.l.: an investor deck, the company website and part of the installation and use manual of the Aliquis© framework software, its flagship product. This dissertation is structured as follows: Chapter 1 presents the project and the company in detail; Chapter 2 outlines the internationalization and globalization processes and the Artificial Intelligence market both in Italy and in China; Chapter 3 provides the theoretical foundations for every aspect related to Specialized Translation, including website localization; Chapter 4 describes the resources and tools used to perform the translations; Chapter 5 proposes an analysis of the source texts; Chapter 6 is a commentary on translation strategies and choices

    An Effective Surface Defect Classification Method Based on RepVGG with CBAM Attention Mechanism (RepVGG-CBAM) for Aluminum Profiles

    Get PDF
    The automatic classification of aluminum profile surface defects is of great significance in improving the surface quality of aluminum profiles in practical production. This classification is influenced by the small and unbalanced number of samples and lack of uniformity in the size and spatial distribution of aluminum profile surface defects. It is difficult to achieve high classification accuracy by directly using the current advanced classification algorithms. In this paper, digital image processing methods such as rotation, flipping, contrast, and luminance transformation were used to augment the number of samples and imitate the complex imaging environment in actual practice. A RepVGG with CBAM attention mechanism (RepVGG-CBAM) model was proposed and applied to classify ten types of aluminum profile surface defects. The classification accuracy reached 99.41%, in particular, the proposed method can perfectly classify six types of defects: concave line (cl), exposed bottom (eb), exposed corner bottom (ecb), mixed color (mc), non-conductivity (nc) and orange peel (op), with 100% precision, recall, and F1. Compared with the existing advanced classification algorithms VGG16, VGG19, ResNet34, ResNet50, ShuffleNet_v2, and basic RepVGG, our model is the best in terms of accuracy, macro precision, macro recall and macro F1, and the accuracy was improved by 4.85% over basic RepVGG. Finally, an ablation experiment proved that the classification ability was strongest when the CBAM attention mechanism was added following Stage 1 to Stage 4 of RepVGG. Overall, the method we proposed in this paper has a significant reference value for classifying aluminum profile surface defects

    AI: Limits and Prospects of Artificial Intelligence

    Get PDF
    The emergence of artificial intelligence has triggered enthusiasm and promise of boundless opportunities as much as uncertainty about its limits. The contributions to this volume explore the limits of AI, describe the necessary conditions for its functionality, reveal its attendant technical and social problems, and present some existing and potential solutions. At the same time, the contributors highlight the societal and attending economic hopes and fears, utopias and dystopias that are associated with the current and future development of artificial intelligence

    PlayMaps - Representation of 3D cartography data in Augmented Reality (AR) games

    Get PDF
    A presente dissertação tem como tema a representação de dados cartográficos 3D em ambientes de Realidade Aumentada (RA) aplicados a tecnologias móveis. No turismo, a escolha de um lugar para visitar pode ser um processo árduo e exaustivo que na maioria das vezes traz contratempos imprevistos. Dada a abundância de informações sobre um local, ou mesmo a falta dela em muitas circunstâncias, é simples para um possível turista ficar desorientado e fazer o julgamento incorreto de não visitá-lo. Em muitos casos, as pessoas até desconhecem o potencial das regiões. Muitos representantes têm lutado para encontrar maneiras de atrair mais turistas para suas cidades, muitas vezes se perguntando: "Como posso promover minha cidade para o mundo de uma maneira mais eficaz?". Obviamente, essa divulgação precisa ser feita de forma segura e acessível. Assim, esta dissertação pretende criar um jogo para adolescentes, entre os 10 e os 15 anos, baseado em Realidade Aumentada (RA), que seja capaz de digitalizar um mapa em papel e permitir ao utilizador interagir com o mesmo. A app terá de proporcionar a componente educativa do território e também um nível adequado de interação com o utilizador. Este aplicativo será fácil de usar e compatível com qualquer sistema operacional móvel. Como tal, foi pensado para que qualquer pessoa com um smartphone possa utilizar esta tecnologia. Além disso, este aplicativo será flexível, adaptável e genérico. Cartografias diferentes exigirão modelos geográficos diferentes ou mesmo metodologias de jogo diferentes. Portanto, este aplicativo terá a capacidade de importar diferentes informações geográficas e criar um jogo específico para essa cartografia. Dois estudos anteriores foram realizados nesta área, nomeadamente para potenciar a experiência de visitas à Galeria da Biodiversidade e ao Jardim Botânico como forma de jogo. O primeiro estudo utiliza o método "case study", utilizando uma abordagem quantitativa e qualitativa para entender como a experiência lúdica proporcionada pela tecnologia de realidade aumentada pode contribuir para a entrega de informações que esses espaços pretendem transmitir aos visitantes {soares2021flo}. O segundo estudo procurou explorar formas de conectar ambientes internos e externos por meio de Realidade Aumentada (RA) {teixeira2021serious}. Esses tipos de abordagens de como disseminar informações são fundamentais para que o usuário tenha uma compreensão adequada do que a região tem a oferecer. Esses recursos serão aplicados ao mapeamento de territórios conhecidos a fim de investigar formas de promover o turismo melhorando e inovando a forma como as pessoas aprendem e exploram novas cidades e outros espaços. Embora esta dissertação seja apenas um caso de estudo, com esta implementação, a solução proposta pode funcionar como base para o desenvolvimento de uma ferramenta universal para qualquer instituição e/ou cidade que se queira promover.The present dissertation has, as its theme, the representation of 3D cartography data in Augmented Reality (AR) environments applied to mobile technologies. In tourism, choosing a place to visit can be a hard and exhaustive process which most times brings unforeseen setbacks. Given the abundance of information about a location, or even the lack thereof in many circumstances, it's simple for a possible tourist to become disoriented and make the incorrect judgement of not visiting it. In many cases, people even are unaware of the regions' potential. Many city officials and space marketers have struggled to find ways to attract more tourists to their cities, often asking themselves, "How can I promote my city to the world in a more effective way?". Obviously, this advertisement needs to be done in a safe and affordable way. Therefore, this dissertation aims to create a game for teens, between 10 and 15 years old, based on Augmented Reality (AR), which is capable to digitise a paper map and allowing the user to interact with it. The app will have to provide the educational component of the territory and also an appropriate level of interaction with the user. This app will be easy to use, user-friendly and compatible with any mobile operating system. As such, it is designed that anyone with a smart phone can use this technology. Furthermore, this app will be flexible, adaptable and generic. Different cartographies will require different geographical models or even different game methodologies. Therefore, this application will have the ability to import different geographic information, and create a specific game to that cartography. Two previous studies were carried out in this area, namely to enhance the experience of visits to Galeria da Biodiversidade and Jardim Botânico as a form of a game. The first study employs the case study method, using a quantitative and qualitative approach to comprehend how the entertaining experience given by augmented reality technology may contribute in the delivery of the information these spaces intend to transmit to visitors {soares2021flo}. The second study sought to explore ways to connect indoor and outdoor environments through Augmented Reality (AR) {teixeira2021serious}. These types of approaches on how to disseminate information are fundamental for the user to have an appropriate grasp of what the region has to offer. These functionalities will be applied to cartography of know territories in order to investigate ways to promote tourism by improving and innovating the way people learn and explore new cities and other spaces. Although this dissertation is only a case study, with this implementation, the proposed solution can become a stepping stone to the development of a universal tool for any institution and/or city that intends to promote itself
    corecore