427 research outputs found

    Instability of computer vision models is a necessary result of the task itself

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    Adversarial examples resulting from instability of current computer vision models are an extremely important topic due to their potential to compromise any application. In this paper we demonstrate that instability is inevitable due to a) symmetries (translational invariance) of the data, b) the categorical nature of the classification task, and c) the fundamental discrepancy of classifying images as objects themselves. The issue is further exacerbated by non-exhaustive labelling of the training data. Therefore we conclude that instability is a necessary result of how the problem of computer vision is currently formulated. While the problem cannot be eliminated, through the analysis of the causes, we have arrived at ways how it can be partially alleviated. These include i) increasing the resolution of images, ii) providing contextual information for the image, iii) exhaustive labelling of training data, and iv) preventing attackers from frequent access to the computer vision system

    The neuropsychology of emotion, and emotion regulation: The role of laterality and hierarchy

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    Over the last few decades, work in affective neuroscience has increasingly investigated the neural basis of emotion. A central debate in the field, when studying individuals with brain damage, has been whether emotional processes are lateralized or not. This review aims to expand this debate, by considering the need to include a hierarchical dimension to the problem. The historical journey of the diverse literature is presented, particularly focusing on the need to develop a research program that explores the neural basis of a wide range of emotional processes (perception, expression, experience, regulation, decision making, etc.), and also its relation to lateralized cortical and deep-subcortical brain structures. Of especial interest is the study of the interaction between emotional components; for example, between emotion generation and emotion regulation. Finally, emerging evidence from lesion studies is presented regarding the neural basis of emotion-regulation strategies, for which the issue of laterality seems most relevant. It is proposed that, because emotion-regulation strategies are complex higher-order cognitive processes, the question appears to be not the lateralization of the entire emotional process, but the lateralization of the specific cognitive tools we use to manage our feelings, in a range of different ways

    Claiming veganism and vegan geographies

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    A decade ago, veganism was a fringe radical movement. It was also largely absent from the geographical discipline, despite a rich history of vegan scholarship being present in disciplines such as Sociology and Psychology. However, veganism has recently seen a surge in popularity, with more people than ever before becoming vegan for a mixture of animal welfare, environmental, and health-based reasons. With this mainstreaming, veganism has become contentious and fiercely defended. As veganism has become a growing social and political force, geographers have started to take notice of this previously fringe movement, which is gaining economic, ecological, and cultural power as investment flows into ‘plant-based’ products and new markets are emerging. In this commentary, we look at how veganism has recently been taken up in Geography via several distinct trends that all stake a claim in defining an emerging geographical sub-discipline, vegan geographies. We note the importance of scholarly pluralism and attention to establishing geographical sub-disciplines more broadly

    Wind optimal flight trajectories to minimise fuel consumption within a 3 dimensional flight network

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    This paper assesses the potential fuel savings benefits that can be gained from wind optimal flight trajectories. This question is posed on a 3 dimensional fixed flight network consisting of discrete waypoints which is representative of the size of Europe. The optimisation implements Dijkstra's shortest path algorithm to compute the minimum fuel burn route through a network and compares this to the fuel burn for the shortest distance route. Particular effort is applied to testing the repeatability and robustness of the results. This is achieved through a sensitive analysis based on a number of identified model parameters relating to the setup of the flight network. The results of this study show fuel savings between 1.0%-10.3%, and suggest that the benefits of wind optimal flight trajectories are significant
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