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Transfer Learning for Facial Emotion Recognition on Small Datasets Paolo Barile , Clara Bassano , Paolo Piciocchi (pages: 1-5) How to Link Educational Purposes and Immersive Video Games Development? An Ontological Approach Proposal Nathan Aky (pages: 6-13) Application of Building Information Modeling (BIM) in the Planning and Construction of a Building Renata Maria Abrantes Baracho , Luiz Gustavo da Silva Santiago , Antonio Tagore Assumpção Mendoza e Silva , Marcelo Franco Porto (pages: 14-19) Transformative, Transdisciplinary, Transcendent Digital Education: Synergy, Sustainability and Calamity Rusudan Makhachashvili , Ivan Semenist (pages: 20-27) New Online Tools for the Data Visualization of Bivalve Molluscs' Production Areas of Veneto Region Eleonora Franzago , Claudia Casarotto , Matteo Trolese , Marica Toson , Mirko Ruzza , Manuela Dalla Pozza , Grazia Manca , Giuseppe Arcangeli , Nicola Ferrè , Laura Bille (pages: 28-32) Geodata Processing Methodology on GIS Platforms When Creating Spatial Development Plans of Territorial Communities: Case of Ukraine Olena Kopishynska , Yurii Utkin , Ihor Sliusar , Leonid Flehantov , Mykola Somych , Oksana Yakovlieva , Olena Scryl (pages: 33-40) D-CIDE: An Interactive Code Learning Program Lukas Grant , Matthew F. Tennyson , Jason Owen (pages: 41-46) Interdisciplinary Digital Skills Development for Educational Communication: Emergency and Ai-Enhanced Digitization Rusudan Makhachashvili , Ivan Semenist , Ganna Prihodko , Irina Kolegaeva , Olexandra Prykhodchenko , Olena Tupakhina (pages: 47-51) Interdisciplinarity in Smart Systems Applied to Rural School Transport in Brazil Renata Maria Abrantes Baracho , Mozart Joaquim Magalhães Vidigal , Marcelo Franco Porto , Beatriz Couto (pages: 52-59) Peculiarities of the Realization of IT Projects for the Implementation of ERP Systems on the Path of Digitalization of Territorial Communities Activities Olena Kopishynska , Yurii Utkin , Ihor Sliusar , Khanlar Makhmudov , Olena Kalashnyk , Svitlana Moroz , Olena Kyrychenko (pages: 60-67)
ABSTRACT
Identifying Reflectors in Seismic Images via Statistic and Syntactic Methods
In geologic interpretation of seismic reflection data, accurate
identification of reflectors is the foremost step to ensure proper
subsurface structural definition. Reflector information, along
with other data sets, is a key factor to predict the presence of
hydrocarbons. In this work, mathematic and pattern recognition
theory was adapted to design two statistical and two syntactic
algorithms which constitute a tool in semiautomatic reflector
identification. The interpretive power of these four schemes
was evaluated in terms of prediction accuracy and
computational speed. Among these, the semblance method was
confirmed to render the greatest accuracy and speed. Syntactic
methods offer an interesting alternative due to their inherently
structural search method.
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