Results 11 to 20 of about 2,754,654 (357)
Unsupervised Learning of Probabilistic Grammar-Markov Models for Object Categories [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008 We introduce a Probabilistic Grammar-Markov Model (PGMM) which couples probabilistic context free grammars and Markov Random Fields. These PGMMs are generative models defined over attributed features and are used to detect and classify objects in natural images.
Long Zhu, Yuanhao Chen, Alan Yuille
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Object classification based on a geometric grammar with a range camera [PDF]
2009 IEEE International Conference on Robotics and Automation, 2009 This paper proposes an object classification framework based on a geometric grammar aimed for mobile robotic applications. The paper first discusses the geometric grammar as a compact representation form for object categories with primitive parts as its constituent elements.
Jiwon Shin +4 more
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Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing [PDF]
Neural Information Processing Systems, 2007 We describe an unsupervised method for learning a probabilistic grammar of an object from a set of training examples. Our approach is invariant to the scale and rotation of the objects. We illustrate our approach using thirteen objects from the Caltech 101 database.
Long Zhu, Yuanhao Chen, Alan Yuille
semanticscholar +5 more sources
A grammar for hierarchical object descriptions in logic programs [PDF]
2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 Modeling objects using formal grammars has recently regained much attention in computer vision. Probabilistic logic programming, such as Bilattice based Logical Reasoning (BLR), is shown to produce impressive results in object detection/recognition. Although hierarchical object descriptions are preferred in high-level vision tasks for several reasons ...
Maneesh Singh +3 more
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plyranges: a grammar of genomic data transformation
Genome Biology, 2019 Bioconductor is a widely used R-based platform for genomics, but its host of complex genomic data structures places a cognitive burden on the user. For most tasks, the GRanges object would suffice, but there are gaps in the API that prevent its general ...
Stuart Lee +2 more
doaj +2 more sources
Process grammar and process history for 2D objects
DAIMI Report Series, 2008 This project is the written report for the course in Picture Processing at the Department of Computer Science, Aarhus University. The starting point is a paper by Michael Leyton in Artificial Intelligence 34, 1988: "A process grammar for shape". The paper describes how it is possible to derive the process history for an object from its state at two ...
Thomas W. Larsen, Brian H. Mayoh
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Grammar and the Formal Identity of Name and Object
Nordic Wittgenstein ReviewIn this paper, I will be arguing that the basic infrastructure of an ineffable formal identity between name and object which is presented in the Tractatus is still very much involved in Wittgenstein's early development of the concept of grammar.
Tal Ben-Itzhak
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Grammatical structures of emoji in Japanese-language text conversations [PDF]
Cognitive ResearchEmojis have become a ubiquitous part of everyday text communication worldwide. Cohn et al. (Cognit Res Princ Implic 4(1):1–18, 2019) studied the grammatical structure of emoji usage among English speakers and found a correlation between the sequence of ...
Kazuki Sekine, Manaka Ikuta
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Formal Verification of Object-Oriented Graph Grammars Specifications
Electronic Notes in Theoretical Computer Science, 2007 AbstractConcurrent object-oriented systems are ubiquitous due to the importance of networks and the current demands for modular, reusable, and easy to develop software. However, checking the correctness of such systems is a hard task, mainly due to concurrency and inheritance aspects.
Ana Paula Lüdtke Ferreira +2 more
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Video-aided Unsupervised Grammar Induction [PDF]
North American Chapter of the Association for Computational Linguistics, 2021 We investigate video-aided grammar induction, which learns a constituency parser from both unlabeled text and its corresponding video. Existing methods of multi-modal grammar induction focus on grammar induction from text-image pairs, with promising ...
Songyang Zhang +5 more
semanticscholar +1 more source