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Multidisciplinary pattern recognition applications: A review
Pattern recognition (PR) is the study of how machines can examine the environment, learn
to distinguish patterns of interest from their background, and make reliable and feasible …
to distinguish patterns of interest from their background, and make reliable and feasible …
Computational and experimental approaches to visual aesthetics
A Brachmann, C Redies - Frontiers in computational neuroscience, 2017 - frontiersin.org
Aesthetics has been the subject of long-standing debates by philosophers and
psychologists alike. In psychology, it is generally agreed that aesthetic experience results …
psychologists alike. In psychology, it is generally agreed that aesthetic experience results …
Fine-tuning convolutional neural networks for fine art classification
The increasing availability of large digitized fine art collections opens new research
perspectives in the intersection of artificial intelligence and art history. Motivated by the …
perspectives in the intersection of artificial intelligence and art history. Motivated by the …
Ceci n'est pas une pipe: A deep convolutional network for fine-art paintings classification
“Ceci n'est pas une pipe” French for “This is not a pipe”. This is the description painted on
the first painting in the figure above. But to most of us, how could this painting is not a pipe …
the first painting in the figure above. But to most of us, how could this painting is not a pipe …
History of art paintings through the lens of entropy and complexity
Art is the ultimate expression of human creativity that is deeply influenced by the philosophy
and culture of the corresponding historical epoch. The quantitative analysis of art is therefore …
and culture of the corresponding historical epoch. The quantitative analysis of art is therefore …
Painting-91: a large scale database for computational painting categorization
Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary
research domain. Most of the research in the analysis of paintings involve medium to small …
research domain. Most of the research in the analysis of paintings involve medium to small …
A dataset and a convolutional model for iconography classification in paintings
Iconography in art is the discipline that studies the visual content of artworks to determine
their motifs and themes and to characterize the way these are represented. It is a subject of …
their motifs and themes and to characterize the way these are represented. It is a subject of …
Classification of artistic styles using binarized features derived from a deep neural network
With the vast expansion of digital contemporary painting collections, automatic theme
stylization has grown in demand in both academic and commercial fields. The recent interest …
stylization has grown in demand in both academic and commercial fields. The recent interest …
A comprehensive survey on object detection in Visual Art: taxonomy and challenge
Cultural heritage data plays a key role in the understanding of past human history and
culture, enriches the present and prepares the future. A wealth of information is buried in …
culture, enriches the present and prepares the future. A wealth of information is buried in …
Architectural style classification using multinomial latent logistic regression
Architectural style classification differs from standard classification tasks due to the rich inter-
class relationships between different styles, such as re-interpretation, revival, and …
class relationships between different styles, such as re-interpretation, revival, and …