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Journal articles on the topic 'Comparative and general Parsing'

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Published: 4 June 2021

Last updated: 6 February 2022

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1

Reeves, J., and R. Pacheco Pardo. "Parsing China's power: Sino-Mongolian and Sino-DPRK relations in comparative perspective." International Relations of the Asia-Pacific 13, no. 3 (May 23, 2013): 449–77. http://dx.doi.org/10.1093/irap/lct007.

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2

Tian, Ying. "Comparative Study on “Sentence Rewriting for Semantic Parsing” and “Graph-Based Translation Via Graph Segmentation”." Journal of Physics: Conference Series 1852, no. 4 (April 1, 2021): 042021. http://dx.doi.org/10.1088/1742-6596/1852/4/042021.

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3

Tierney, Ann Jane. "Feeding, hunger, satiety and serotonin in invertebrates." Proceedings of the Royal Society B: Biological Sciences 287, no. 1932 (August 12, 2020): 20201386. http://dx.doi.org/10.1098/rspb.2020.1386.

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The serotonergic modulation of feeding behaviour has been intensively studied in several invertebrate groups, including Arthropoda, Annelida, Nematoda and Mollusca. These studies offer comparative information on feeding regulation across divergent phyla and also provide general insights into the neural control of feeding. Specifically, model invertebrates are ideal for parsing feeding behaviour into component parts and examining the underlying mechanisms at the levels of biochemical pathways, single cells and identified neural circuitry. Research has found that serotonin is crucial during certain phases of feeding behaviour, especially movements directly underlying food intake, but inessential during other phases. In addition, while the serotonin system can be manipulated systemically in many animals, invertebrate model organisms also allow manipulations at the level of single cells and molecules, revealing limited and precise serotonergic actions. The latter highlight the importance of local versus global modulatory effects of serotonin, a potentially significant consideration for drug and pesticide design.

4

Shao, Zhenfeng, Zifan Zhou, Xiao Huang, and Ya Zhang. "MRENet: Simultaneous Extraction of Road Surface and Road Centerline in Complex Urban Scenes from Very High-Resolution Images." Remote Sensing 13, no. 2 (January 12, 2021): 239. http://dx.doi.org/10.3390/rs13020239.

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Automatic extraction of the road surface and road centerline from very high-resolution (VHR) remote sensing images has always been a challenging task in the field of feature extraction. Most existing road datasets are based on data with simple and clear backgrounds under ideal conditions, such as images derived from Google Earth. Therefore, the studies on road surface extraction and road centerline extraction under complex scenes are insufficient. Meanwhile, most existing efforts addressed these two tasks separately, without considering the possible joint extraction of road surface and centerline. With the introduction of multitask convolutional neural network models, it is possible to carry out these two tasks simultaneously by facilitating information sharing within a multitask deep learning model. In this study, we first design a challenging dataset using remote sensing images from the GF-2 satellite. The dataset contains complex road scenes with manually annotated images. We then propose a two-task and end-to-end convolution neural network, termed Multitask Road-related Extraction Network (MRENet), for road surface extraction and road centerline extraction. We take features extracted from the road as the condition of centerline extraction, and the information transmission and parameter sharing between the two tasks compensate for the potential problem of insufficient road centerline samples. In the network design, we use atrous convolutions and a pyramid scene parsing pooling module (PSP pooling), aiming to expand the network receptive field, integrate multilevel features, and obtain more abundant information. In addition, we use a weighted binary cross-entropy function to alleviate the background imbalance problem. Experimental results show that the proposed algorithm outperforms several comparative methods in the aspects of classification precision and visual interpretation.

5

Hinnells, John R. "South Asian Diaspora Communities and Their Religion: a Comparative Study of Parsi Experiences." South Asia Research 14, no. 1 (April 1994): 62–104. http://dx.doi.org/10.1177/026272809401400104.

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6

Traxler, Matthew J. "Parsing." Wiley Interdisciplinary Reviews: Cognitive Science 2, no. 4 (October 27, 2010): 353–64. http://dx.doi.org/10.1002/wcs.112.

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7

Gmyrya, Ludmila B., and Yusup A. Magomedov. "THE SPECIFICITY OF THE CERAMIC COMPLEXES ISOLATED BURIAL GROUPS NO. 1-4 NORTHERN SECTION OF THE PALACE SYRTSOVA BURIAL GROUND (EXCAVATIONS 1982-1985)." History, Archeology and Ethnography of the Caucasus 15, no. 3 (October 14, 2019): 435–70. http://dx.doi.org/10.32653/ch153435-470.

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The article deals with the specifics of the ceramic collection of 4 separate groups of burials (№1-4) of the Northern section of the Palace-Syrt burial ground of the IV–V centuries (hereinafter – the Northern Palace-Syrt), the excavations of which were carried out in 1982-1985. the Purpose of the study is to identify the features of this ceramic complex and to compare the data with the available results of the classification of ceramics of the barrow groups of the southern section of the burial ground (hereinafter – the southern Palace-Syrt), which was studied in 2009-2016.Separate burial mounds are essentially closed collective burial complexes connected by common social factors. Analysis of materials, such as certain groups of graves, and the comparative parsing of the entire series of mound groups located in the same area of the burial ground (planigraphy burials, funeral rites, especially the inventory, etc.), allows to determine in the burial traditions of the manifestations of the social structure of the population, and to identify common and particular in the ethnic composition of a large Union of tribes. The method of step analysis of the ceramic collection of burial mounds groups used in this work: burial – group of burials – group of burials of a separate certain area of the burial ground – group of burials of 2 sites of the burial ground, tested on the materials of the southern Palace-Syrt. It allows us to record both the General trends in the formation of the ceramic complex among the socially distinguished population, and to identify the principles of creating a clothing component of the funeral rite of the population. The authors give the characteristics of the sets of ceramics of each of the groups of burials of the Northern Palace-Syrt, on the basis of which a summary classification of the entire collection of ceramics is carried out. According to the authors ' conclusion, in the barrow groups №1-4 of the Northern Palace-Syrt there was no typological monotony of ceramic vessels, both in the sets of dishes of individual burial groups.

8

SACKLEY, NICOLE. "COSMOPOLITANISM AND THE USES OF TRADITION: ROBERT REDFIELD AND ALTERNATIVE VISIONS OF MODERNIZATION DURING THE COLD WAR." Modern Intellectual History 9, no. 3 (November 2012): 565–95. http://dx.doi.org/10.1017/s1479244312000200.

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The history of the rise and fall of “modernization theory” after World War II has been told as a story of Talcott Parsons, Walt Rostow, and other US social scientists who built a general theory in US universities and sought to influence US foreign policy. However, in the 1950s anthropologist Robert Redfield and his Comparative Civilizations project at the University of Chicago produced an alternative vision of modernization—one that emphasized intellectual conversation across borders, the interrelation of theory and fieldwork, and dialectical relations of tradition and modernity. In tracing the Redfield project and its legacies, this essay aims to broaden intellectual historians’ sense of the complexity, variation, and transnational currents within postwar American discourse about modernity and tradition.

9

Berridge, Kent C., and Terry E. Robinson. "Parsing reward." Trends in Neurosciences 26, no. 9 (September 2003): 507–13. http://dx.doi.org/10.1016/s0166-2236(03)00233-9.

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10

Hirst, William. "Parsing Memory." Contemporary Psychology: A Journal of Reviews 41, no. 4 (April 1996): 339–40. http://dx.doi.org/10.1037/002862.

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11

Treadway, Michael T., and David H. Zald. "Parsing Anhedonia." Current Directions in Psychological Science 22, no. 3 (June 2013): 244–49. http://dx.doi.org/10.1177/0963721412474460.

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12

KIM, JONG-BOK, Jaehyung Yang, and sanghoun Song. "Parsing Korean Comparative Constructions in a Typed-Feature Structure Grammar." Language and Information 14, no. 1 (June 30, 2010): 1–24. http://dx.doi.org/10.29403/li.14.1.1.

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13

Dietrich, Michael R. "Parsing postgenomics." Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 59 (October 2016): 158–60. http://dx.doi.org/10.1016/j.shpsc.2016.03.005.

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14

Gulordava, Kristina, and Paola Merlo. "Multi-lingual Dependency Parsing Evaluation: a Large-scale Analysis of Word Order Properties using Artificial Data." Transactions of the Association for Computational Linguistics 4 (December 2016): 343–56. http://dx.doi.org/10.1162/tacl_a_00103.

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The growing work in multi-lingual parsing faces the challenge of fair comparative evaluation and performance analysis across languages and their treebanks. The difficulty lies in teasing apart the properties of treebanks, such as their size or average sentence length, from those of the annotation scheme, and from the linguistic properties of languages. We propose a method to evaluate the effects of word order of a language on dependency parsing performance, while controlling for confounding treebank properties. The method uses artificially-generated treebanks that are minimal permutations of actual treebanks with respect to two word order properties: word order variation and dependency lengths. Based on these artificial data on twelve languages, we show that longer dependencies and higher word order variability degrade parsing performance. Our method also extends to minimal pairs of individual sentences, leading to a finer-grained understanding of parsing errors.

15

Schwartz, Russell. "Haplotype Parsing." Applied Bioinformatics 3, no. 2 (2004): 181–91. http://dx.doi.org/10.2165/00822942-200403020-00012.

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16

Howland, Robert H. "The Comparative Cardiac Effects of Haloperidol and Quetiapine: Parsing a Review." Journal of Psychosocial Nursing and Mental Health Services 52, no. 6 (June 1, 2014): 23–26. http://dx.doi.org/10.3928/02793695-20140515-01.

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17

Grapin-Botton, Anne, and Palle Serup. "Parsing the Pancreas." New England Journal of Medicine 376, no. 9 (March 2, 2017): 886–88. http://dx.doi.org/10.1056/nejmcibr1616217.

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18

Rallu, Murielle, Joshua G. Corbin, and Gord Fishell. "Parsing the prosencephalon." Nature Reviews Neuroscience 3, no. 12 (December 2002): 943–51. http://dx.doi.org/10.1038/nrn989.

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19

Sun, Weiwei, and Xiaojun Wan. "Data-driven, PCFG-based and Pseudo-PCFG-based Models for Chinese Dependency Parsing." Transactions of the Association for Computational Linguistics 1 (December 2013): 301–14. http://dx.doi.org/10.1162/tacl_a_00229.

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We present a comparative study of transition-, graph- and PCFG-based models aimed at illuminating more precisely the likely contribution of CFGs in improving Chinese dependency parsing accuracy, especially by combining heterogeneous models. Inspired by the impact of a constituency grammar on dependency parsing, we propose several strategies to acquire pseudo CFGs only from dependency annotations. Compared to linguistic grammars learned from rich phrase-structure treebanks, well designed pseudo grammars achieve similar parsing accuracy and have equivalent contributions to parser ensemble. Moreover, pseudo grammars increase the diversity of base models; therefore, together with all other models, further improve system combination. Based on automatic POS tagging, our final model achieves a UAS of 87.23%, resulting in a significant improvement of the state of the art.

20

Winkler, Peter. "Puzzled: Parsing partitions." Communications of the ACM 54, no. 2 (February 2011): 112. http://dx.doi.org/10.1145/1897816.1897845.

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21

Peyton Jones, Simon L. "Parsing distfix operators." Communications of the ACM 29, no. 2 (February 1986): 118–22. http://dx.doi.org/10.1145/5657.5659.

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22

Aycock, J. "Practical Earley Parsing." Computer Journal 45, no. 6 (June 1, 2002): 620–30. http://dx.doi.org/10.1093/comjnl/45.6.620.

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23

Mullard, Asher. "Parsing exceptional responders." Nature Reviews Drug Discovery 20, no. 1 (December 4, 2020): 8. http://dx.doi.org/10.1038/d41573-020-00214-w.

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24

Lobina, David J., José E. García-Albea, and Josep Demestre. "Parsing for Position." Experimental Psychology 67, no. 1 (January 2020): 40–47. http://dx.doi.org/10.1027/1618-3169/a000477.

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Abstract. Monitoring tasks have long been employed in psycholinguistics, and the end-of-clause effect is possibly the better-known result of using this technique in the study of parsing. Recent results with the tone-monitoring task suggest that tone position modulates cognitive load, as reflected in reaction times (RTs): the earlier the tone appears in a sentence, the longer the RTs. In this study, we show that verb position is also an important factor. In particular, changing the time/location at which verb–noun(s) dependencies are computed during the processing of a sentence has a clear effect on cognitive load and, as a result, on the resources that can be devoted to monitoring and responding to a tone. This study is based on two pieces of evidence. We first report the acceptability ratings of six word orders in Spanish and then present monitoring data with three of these different word orders. Our results suggest that RTs tend to be longer if the verb is yet to be processed, pointing to the centrality of a sentence’s main verb in parsing in general.

25

Sherr, Charles J. "Parsing Ink4a/Arf." Cell 106, no. 5 (September 2001): 531–34. http://dx.doi.org/10.1016/s0092-8674(01)00486-x.

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26

Megacz, Adam. "Scannerless Boolean Parsing." Electronic Notes in Theoretical Computer Science 164, no. 2 (October 2006): 97–102. http://dx.doi.org/10.1016/j.entcs.2006.10.007.

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27

Thiemann, Peter, and Matthias Neubauer. "Parameterized LR Parsing." Electronic Notes in Theoretical Computer Science 110 (December 2004): 115–32. http://dx.doi.org/10.1016/j.entcs.2004.06.007.

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28

Cockshott, W. P., and P. W. Foulk. "Parsing instruction set computers." IEE Proceedings E Computers and Digital Techniques 138, no. 5 (1991): 305. http://dx.doi.org/10.1049/ip-e.1991.0042.

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29

Paris, Scott G. "Parsing the Child's Mind." Contemporary Psychology 44, no. 3 (June 1999): 202–4. http://dx.doi.org/10.1037/001996.

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30

McCord, M. C., J. W. Murdock, and B. K. Boguraev. "Deep parsing in Watson." IBM Journal of Research and Development 56, no. 3.4 (May 2012): 3:1–3:15. http://dx.doi.org/10.1147/jrd.2012.2185409.

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31

Nigel Horspool, R. "Recursive ascent-descent parsing." Computer Languages 18, no. 1 (January 1993): 1–15. http://dx.doi.org/10.1016/0096-0551(93)90027-x.

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32

Viswanathan, N., and Y. N. Srikant. "Parallel incremental LR parsing." Computer Languages 20, no. 3 (August 1994): 151–75. http://dx.doi.org/10.1016/0096-0551(94)90002-7.

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33

Wang, Erlu, Priyan Malarvizhi Kumar, and R. Dinesh Jackson samuel. "Semantic Graphical Dependence Parsing Model in Improving English Teaching Abilities." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 3 (May 30, 2021): 1–14. http://dx.doi.org/10.1145/3425633.

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It is a very difficult problem to achieve high-order functionality for graphical dependency parsing without growing decoding difficulties. To solve this problem, this article offers a way for Semantic Graphical Dependence Parsing Model (SGDPM) with a language-dependency model and a beam search to represent high-order functions for computer applications. The first approach is to scan a large amount of unnoticed data using a baseline parser. It will build auto-parsed data to create the Language-dependence Model (LDM). The LDM is based on a set of new features during beam search decoding, where it will incorporate the LDM features into the parsing model and utilize the features in parsing models of bilingual text. Our approach has main benefits, which include rich high-order features that are described given the large size and the additional large crude corpus for increasing the difficulty of decoding. Further, SGDPM has been evaluated using the suggested method for parsing tasks of mono-parsing text and bi-parsing text to carry out experiments on the English and Chinese data in the mono-parsing text function using computer applications. Experimental results show that the most accurate Chinese data is obtained with the best known English data systems and their comparable accuracy. Furthermore, the lab-scale experiments on the Chinese/General bilingual information in the bitext parsing process outperform the best recorded existing solutions.

34

Gentleman, Darcy J. "Parsing Sustainability — Part 1." Environmental Science & Technology 44, no. 5 (March 2010): 1515. http://dx.doi.org/10.1021/es100315v.

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35

Byrne, R. W. "Imitation as behaviour parsing." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 358, no. 1431 (February 4, 2003): 529–36. http://dx.doi.org/10.1098/rstb.2002.1219.

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Non–human great apes appear to be able to acquire elaborate skills partly by imitation, raising the possibility of the transfer of skill by imitation in animals that have only rudimentary mentalizing capacities: in contrast to the frequent assumption that imitation depends on prior understanding of others' intentions. Attempts to understand the apes' behaviour have led to the development of a purely mechanistic model of imitation, the ‘behaviour parsing’ model, in which the statistical regularities that are inevitable in planned behaviour are used to decipher the organization of another agent's behaviour, and thence to imitate parts of it. Behaviour can thereby be understood statistically in terms of its correlations (circumstances of use, effects on the environment) without understanding of intentions or the everyday physics of cause–and–effect. Thus, imitation of complex, novel behaviour may not require mentalizing, but conversely behaviour parsing may be a necessary preliminary to attributing intention and cause.

36

Gómez-Rodríguez, Carlos, Miguel A. Alonso, and Manuel Vilares. "Error-repair parsing schemata." Theoretical Computer Science 411, no. 7-9 (February 2010): 1121–39. http://dx.doi.org/10.1016/j.tcs.2009.12.007.

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37

Rayner, Keith, and Lyn Frazier. "Parsing Temporarily Ambiguous Complements." Quarterly Journal of Experimental Psychology Section A 39, no. 4 (November 1987): 657–73. http://dx.doi.org/10.1080/14640748708401808.

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Holmes, Kennedy and Murray (1987) recently claimed that the empirical support for the Minimal Attachment Strategy of sentence parsing had been weakened by results they reported. They found that reading time for an ambiguous string of words did not decrease when it was preceded by an overt complementizer, which should have disambiguated it. Thus, they suggested that results that we (Frazier and Rayner, 1982) earlier attributed to Minimal Attachment were not due to “garden-path” effects, but rather reflected the extra complexity caused by having to process two sets of clausal relations instead of just one. In the present experiment, we replicated their experiment using eye movement data rather than the subject-paced reading task they used. We found that readers processed Nonminimal Attachment sentences with overt complementizers considerably faster than those without a complementizer. Our results showed that the complexity of Nonminimal Attachment sentences cannot be attributed to their clausal status per se. Differences between the tasks that might contribute to the different pattern of results across the experiments are discussed.

38

Huang, Qiuping, Liangye He, Derek F. Wong, and Lidia S. Chao. "Chinese Unknown Word Recognition for PCFG-LA Parsing." Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/959328.

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This paper investigates the recognition of unknown words in Chinese parsing. Two methods are proposed to handle this problem. One is the modification of a character-based model. We model the emission probability of an unknown word using the first and last characters in the word. It aims to reduce the POS tag ambiguities of unknown words to improve the parsing performance. In addition, a novel method, using graph-based semisupervised learning (SSL), is proposed to improve the syntax parsing of unknown words. Its goal is to discover additional lexical knowledge from a large amount of unlabeled data to help the syntax parsing. The method is mainly to propagate lexical emission probabilities to unknown words by building the similarity graphs over the words of labeled and unlabeled data. The derived distributions are incorporated into the parsing process. The proposed methods are effective in dealing with the unknown words to improve the parsing. Empirical results for Penn Chinese Treebank and TCT Treebank revealed its effectiveness.

39

Taveggia, Carla, and James L. Salzer. "PARsing the events of myelination." Nature Neuroscience 10, no. 1 (January 2007): 17–18. http://dx.doi.org/10.1038/nn0107-17.

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40

Cao, Junjie, Zi Lin, Weiwei Sun, and Xiaojun Wan. "Comparing Knowledge-Intensive and Data-Intensive Models for English Resource Semantic Parsing." Computational Linguistics 47, no. 1 (March 2021): 43–68. http://dx.doi.org/10.1162/coli_a_00395.

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Abstract In this work, we present a phenomenon-oriented comparative analysis of the two dominant approaches in English Resource Semantic (ERS) parsing: classic, knowledge-intensive and neural, data-intensive models. To reflect state-of-the-art neural NLP technologies, a factorization-based parser is introduced that can produce Elementary Dependency Structures much more accurately than previous data-driven parsers. We conduct a suite of tests for different linguistic phenomena to analyze the grammatical competence of different parsers, where we show that, despite comparable performance overall, knowledge- and data-intensive models produce different types of errors, in a way that can be explained by their theoretical properties. This analysis is beneficial to in-depth evaluation of several representative parsing techniques and leads to new directions for parser development.

41

Klimovich-Gray, Anastasia, Mirjana Bozic, and William D. Marslen-Wilson. "Domain-specific and Domain-general Processing in Left Perisylvian Cortex: Evidence from Russian." Journal of Cognitive Neuroscience 29, no. 2 (February 2017): 382–97. http://dx.doi.org/10.1162/jocn_a_01047.

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The processing of words containing inflectional affixes triggers morphophonological parsing and affix-related grammatical information processing. Increased perceptual complexity related to stem-affix parsing is hypothesized to create predominantly domain-general processing demands, whereas grammatical processing primarily implicates domain-specific linguistic demands. Exploiting the properties of Russian morphology and syntax, we designed an fMRI experiment to separate out the neural systems supporting these two demand types, contrasting inflectional complexity, syntactic (phrasal) complexity, and derivational complexity in three comparisons: (a) increase in parsing demands while controlling for grammatical complexity (inflections vs. phrases), (b) increase in grammatical processing demands, and (c) combined demands of morphophonological parsing and grammatical processing (inflections and phrases vs. derivations). Left inferior frontal and bilateral temporal areas are most active when the two demand types are combined, with inflectional and phrasal complexity contrasting strongly with derivational complexity (which generated only bilateral temporal activity). Increased stem-affix parsing demands alone did not produce unique activations, whereas grammatical structure processing activated bilateral superior and middle temporal areas. Selective left frontotemporal language system engagement for short phrases and inflections seems to be driven by simultaneous and interdependent domain-general and domain-specific processing demands.

42

EMBER, LOIS R. "PARSING THE MEANINGS OF WMD." Chemical & Engineering News 84, no. 22 (May 29, 2006): 21–22. http://dx.doi.org/10.1021/cen-v084n022.p021.

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43

Ford, Bridget. "Parsing the History of Emancipation." Reviews in American History 31, no. 2 (2003): 228–35. http://dx.doi.org/10.1353/rah.2003.0028.

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44

Dykes, Natalie, Stefan Evert, Merlin Göttlinger, Philipp Heinrich, and Lutz Schröder. "Argument parsing via corpus queries." it - Information Technology 63, no. 1 (February 1, 2021): 31–44. http://dx.doi.org/10.1515/itit-2020-0051.

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Abstract We present an approach to extracting arguments from social media, exemplified by a case study on a large corpus of Twitter messages collected under the #Brexit hashtag during the run-up to the referendum in 2016. Our method is based on constructing dedicated corpus queries that capture predefined argumentation patterns following standard Walton-style argumentation schemes. Query matches are transformed directly into logical patterns, i. e. formulae with placeholders in a general form of modal logic. We prioritize precision over recall, exploiting the fact that the sheer size of the corpus still delivers substantial numbers of matches for all patterns, and with the goal of eventually gaining an overview of widely-used arguments and argumentation schemes. We evaluate our approach in terms of recall on a manually annotated gold standard of 1000 randomly selected tweets for three selected high-frequency patterns. We also estimate precision by manual inspection of query matches in the entire corpus. Both evaluations are accompanied by an analysis of inter-annotator agreement between three independent judges.

45

Schneider, Karl-Michael. "Tabular parsing and algebraic transformations." Theoretical Computer Science 293, no. 2 (February 2003): 365–89. http://dx.doi.org/10.1016/s0304-3975(01)00352-8.

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46

Clément, Julien, Jean-Pierre Duval, Giovanna Guaiana, Dominique Perrin, and Giuseppina Rindone. "Parsing with a finite dictionary." Theoretical Computer Science 340, no. 2 (June 2005): 432–42. http://dx.doi.org/10.1016/j.tcs.2005.03.030.

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47

Palm, Adi. "Model Theoretic Syntax and Parsing." Electronic Notes in Theoretical Computer Science 53 (April 2004): 261–73. http://dx.doi.org/10.1016/s1571-0661(05)82588-5.

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48

Clifton, Charles. "Thematic roles in sentence parsing." Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale 47, no. 2 (1993): 222–46. http://dx.doi.org/10.1037/h0078817.

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49

Wang, Wei, Yuan Xu, Yingchao Ren, and Gang Wang. "Parsing of Urban Facades from 3D Point Clouds Based on a Novel Multi-View Domain." Photogrammetric Engineering & Remote Sensing 87, no. 4 (April 1, 2021): 283–93. http://dx.doi.org/10.14358/pers.87.4.283.

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Recently, performance improvement in facade parsing from 3D point clouds has been brought about by designing more complex network structures, which cost huge computing resources and do not take full advantage of prior knowledge of facade structure. Instead, from the perspective of data distribution, we construct a new hierarchical mesh multi-view data domain based on the characteristics of facade objects to achieve fusion of deep-learning models and prior knowledge, thereby significantly improving segmentation accuracy. We comprehensively evaluate the current mainstream method on the RueMonge 2014 data set and demonstrate the superiority of our method. The mean intersection-over-union index on the facade-parsing task reached 76.41%, which is 2.75% higher than the current best result. In addition, through comparative experiments, the reasons for the performance improvement of the proposed method are further analyzed.

50

Stowell, Hilton. "Cerebral Slow Waves and Time Parsing." International Journal of Neuroscience 32, no. 3-4 (January 1987): 861–74. http://dx.doi.org/10.3109/00207458709043341.

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