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2017


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Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art

Janai, J., Güney, F., Behl, A., Geiger, A.

Arxiv, 2017 (article)

Abstract
Recent years have witnessed amazing progress in AI related fields such as computer vision, machine learning and autonomous vehicles. As with any rapidly growing field, however, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several topic specific survey papers have been written, to date no general survey on problems, datasets and methods in computer vision for autonomous vehicles exists. This paper attempts to narrow this gap by providing a state-of-the-art survey on this topic. Our survey includes both the historically most relevant literature as well as the current state-of-the-art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding and end-to-end learning. Towards this goal, we first provide a taxonomy to classify each approach and then analyze the performance of the state-of-the-art on several challenging benchmarking datasets including KITTI, ISPRS, MOT and Cityscapes. Besides, we discuss open problems and current research challenges. To ease accessibility and accommodate missing references, we will also provide an interactive platform which allows to navigate topics and methods, and provides additional information and project links for each paper.

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Embedded interruptions and task complexity influence schema-related cognitive load progression in an abstract learning task

Wirzberger, M., Bijarsari, S. E., Rey, G. D.

Acta Psychologica, 179, pages: 30-41, Elsevier, 2017 (article)

Abstract
Cognitive processes related to schema acquisition comprise an essential source of demands in learning situations. Since the related amount of cognitive load is supposed to change over time, plausible temporal models of load progression based on different theoretical backgrounds are inspected in this study. A total of 116 student participants completed a basal symbol sequence learning task, which provided insights into underlying cognitive dynamics. Two levels of task complexity were determined by the amount of elements within the symbol sequence. In addition, interruptions due to an embedded secondary task occurred at five predefined stages over the task. Within the resulting 2x5-factorial mixed between-within design, the continuous monitoring of efficiency in learning performance enabled assumptions on relevant resource investment. From the obtained results, a nonlinear change of learning efficiency over time seems most plausible in terms of cognitive load progression. Moreover, different effects of the induced interruptions show up in conditions of task complexity, which indicate the activation of distinct cognitive mechanisms related to structural aspects of the task. Findings are discussed in the light of evidence from research on memory and information processing.

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DOI [BibTex]

DOI [BibTex]


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Empirical Evidence for Resource-Rational Anchoring and Adjustment

Lieder, F., Griffiths, T. L., Huys, Q. J. M., Goodman, N. D.

Psychonomic Bulletin \& Review, 25, pages: 775-784, Springer, 2017 (article)

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[BibTex]

[BibTex]


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Strategy selection as rational metareasoning

Lieder, F., Griffiths, T.

Psychological Review, 124, pages: 762-794, American Psychological Association, 2017 (article)

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Project Page [BibTex]

Project Page [BibTex]


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A computerized training program for teaching people how to plan better

Lieder, F., Krueger, P. M., Callaway, F., Griffiths, T. L.

PsyArXiv, 2017 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Toward a rational and mechanistic account of mental effort

Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T., Cohen, J., Botvinick, M.

Annual Review of Neuroscience, 40, pages: 99-124, Annual Reviews, 2017 (article)

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Project Page [BibTex]

Project Page [BibTex]


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The anchoring bias reflects rational use of cognitive resources

Lieder, F., Griffiths, T. L., Huys, Q. J. M., Goodman, N. D.

Psychonomic Bulletin \& Review, 25, pages: 762-794, Springer, 2017 (article)

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[BibTex]

[BibTex]