Catalogue Search | MBRL
Search Results Heading
Explore the vast range of titles available.
MBRLSearchResults
-
DisciplineDiscipline
-
Is Peer ReviewedIs Peer Reviewed
-
Reading LevelReading Level
-
Content TypeContent Type
-
YearFrom:-To:
-
More FiltersMore FiltersItem TypeIs Full-Text AvailableSubjectPublisherSourceDonorLanguagePlace of PublicationContributorsLocation
Done
Filters
Reset
13
result(s) for
"Berezowski, Leszek"
Sort by:
Semantic Segmentation (U-Net) of Archaeological Features in Airborne Laser Scanning—Example of the Białowieża Forest
by
Zapłata, Rafał
,
Stereńczak, Krzysztof
,
Mielcarek, Miłosz
in
Agricultural land
,
Airborne lasers
,
ancient field systems
2022
Airborne Laser Scanning (ALS) technology can be used to identify features of terrain relief in forested areas, possibly leading to the discovery of previously unknown archaeological monuments. Spatial interpretation of numerous objects with various shapes and sizes is a difficult challenge for archaeologists. Mapping structures with multiple elements whose area can exceed dozens of hectares, such as ancient agricultural field systems, is very time-consuming. These archaeological sites are composed of a large number of embanked fields, which together form a recognizable spatial pattern. Image classification and segmentation, as well as object recognition, are the most important tasks for deep learning neural networks (DLNN) and therefore they can be used for automatic recognition of archaeological monuments. In this study, a U-Net neural network was implemented to perform semantic segmentation of the ALS-derived data including (1) archaeological, (2) natural and (3) modern features in the Polish part of the Białowieża Forest. The performance of the U-Net segmentation model was evaluated by measuring the pixel-wise similarity between ground truth and predicted segmentation masks. After 83 epochs, The Dice-Sorensen coefficient (F1 score) and the Intersect Over Union (IoU) metrics were 0.58 and 0.5, respectively. The IoU metric reached a value of 0.41, 0.62 and 0.62 for the ancient field system banks, ancient field system plots and burial mounds, respectively. The results of the U-Net deep learning model proved very useful in semantic segmentation of images derived from ALS data.
Journal Article
The Myth of the Zero Article
2011,2009
The zero article is a staple element of any description of English article usage from advanced research publications down to student grammars, but there has been very little inquiry into its meaning and its other properties.ÃÂ There are copious amounts of publications dealing with the definite and indefinite articles but none about the zero article. ÃÂ BerezowskiÃÂ investigates the origin of the concept of the zero article and shows that it has roots both in structural linguistics of the 1940s and earlier historical linguistics. Structural linguists went on to claim that, since the use of articles in English is deemed 'obligatory', the zero article exists but it has no overt form.ÃÂ Looking through earlier attempts at analyzing the meaning of the zero article, from Jespersen to Chesterman, Berezowksi shows how they all fail. An answer to theoretical problems of grammaticalization are developed; it is shown that English articles have not yet reached a stage in their development where their use has spread to all grammatical environments.ÃÂ Thus, a model is developed for determining when there is no article in English.ÃÂ The new model is tested against a commonly occurring case of zero article, using a corpus-based approach. The Myth of the Zero Article will appeal to academics and students interested in grammar and syntax.ÃÂ It covers an issue recurrent in the teaching and learning of English as Second/Foreign language, and will also appeal to teacher trainers and trainee teachers.