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Wyniki wyszukiwania dla: semantic segmentation
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Quantum aspects of semantic analysis and symbolic artificial intelligence.
PublikacjaNowoczesne podejścia do analizy semantycznej, jeśli przeformułować je w język przestrzeni Hilberta, ujawniają formalne struktury znane z mechaniki kwantowej. Podobna sytuacja występuje w rozproszonych reprezentacjach struktur poznawczych rozwijanych na użytek sieci neuronowych. W pracy przyglądamy się różnicom i podobieństwom owych teorii do kwantowej teorii informacji.
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Development and Research of the Text Messages Semantic Clustering Methodology
PublikacjaThe methodology of semantic clustering analysis of customer’s text-opinions collection is developed. The author's version of the mathematical models of formalization and practical realization of short textual messages semantic clustering procedure is proposed, based on the customer’s text-opinions collection Latent Semantic Analysis knowledge extracting method. An algorithm for semantic clustering of the text-opinions is developed,...
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Cooperative Word Net Editor for Lexical Semantic Acquisition
PublikacjaThe article describes an approach for building Word Net semantic dictionary in a collaborative approach paradigm. The presented system system enables functionality for gathering lexical data in a Wikipedia-like style. The core of the system is a user-friendly interface based on component for interactive graph navigation. The component has been used for Word Net semantic network presentation on web page, and it brings functionalities...
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Semantic rules representation in controlled natural language in FluentEditor
PublikacjaThis paper presents a way of representation of semantic rules (SWRL) in controlled English in order to facilitate understanding the rules by humans interacting with a machine. This approach (implemented in FluentEditor) may be applied in many domains, where the understandability of the rules used to support a decision process is of great importance.
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Semantic Driven Table Understanding in Born-Digital Documents
PublikacjaThis paper presents a new approach to table understanding, suitable for born-digital PDF documents. Advance beyond the current state of the art in table understanding is provided by the proposed reverse MVC method, which takes advantage of only partial logic structure loss (degradation) in born-digital PDF documents, as opposed to unrecoverable loss (deterioration) taking place in scan based PDF documents.
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A Semantic Algebra for Modularized Description Logics Knowledge Bases
PublikacjaPublikacja wprowadza pojęcia modularyzacji ontologii opartej na tzw. modułach semantycznych (s-modułach) oraz algebry s-modułów. W pracy zawarto szereg twierdzeń opisujących właściwości algebry, jej związku z klasą algebr cylindrycznych oraz przedyskutowano możliwości zastosowania prezentowanych idei.
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Semantic Analysis and Text Summarization in Socio-Technical Systems
PublikacjaIn this chapter the authors present the results of the development the methodology for increasing the reliability of the functioning of the Socio-Technical System. The existed methods and algorithms for processing unstructured (textual) information were studied. Taking into account noted above strengths and weaknesses of Discriminant and Probabilistic approaches of Latent Semantic Relations analysis in of the summarization projection...
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International Journal of Semantic Computing
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Process Control in Food Fermentation
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Measures for Evaluation of Structure and Semantics of Ontologies
PublikacjaArtykuł przedstawia zagadnienie miar jakości ontologii ze szczególnym uwzględnieniem ich podziału na syntaktyczne (strukturalne) i semantyczne. Na tym tle przedstawione jest nowe podejście do pomiaru właściwości semantycznych ontologii bazujące na kartografii wiedzy.
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Journal of Literary Semantics
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Quaderni di semantica
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Journal on Data Semantics
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Journal of Biomedical Semantics
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Natural Language Semantics
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Journal of Web Semantics
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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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MEAN SHIFT BASED SEGMENTATION FOR BLEEDING REGIONS IN ENDOSCOPIC VIDEOS
PublikacjaWith a set of 38 manually marked bleeding regions form endoscopic videos, the authors attempted to find an optimal image segmentation method for reproducing doctor’s markup. Mean shift segmentation combined with HSV histogram segmentation were used as a segmentation method, which was then optimized by tuning the parameters of the method using global optimization algorithm. A target function for measuring the quality of segmentation was...
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Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublikacjaIn this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...
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Examining Quality of Hand Segmentation Based on Gaussian Mixture Models
PublikacjaResults of examination of various implementations of Gaussian mix-ture models are presented in the paper. Two of the implementations belonged to the Intel’s OpenCV 2.4.3 library and utilized Background Subtractor MOG and Background Subtractor MOG2 classes. The third implementation presented in the paper was created by the authors and extended Background Subtractor MOG2 with the possibility of operating on the scaled version of...
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Accelerating Video Frames Classification With Metric Based Scene Segmentation
PublikacjaThis paper addresses the problem of the efficient classification of images in a video stream in cases, where all of the video has to be labeled. Realizing the similarity of consecutive frames, we introduce a set of simple metrics to measure that similarity. To use these observations for decreasing the number of necessary classifications, we propose a scene segmentation algorithm. Performed experiments have evaluated the acquired...
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Multi-objective design of miniaturized impedance transformers by domain segmentation
PublikacjaFast multi-objective design optimization of compact microstrip impedance transformers is discussed. Our approach exploits approximation models constructed using sampled coarse- mesh EM simulation data in a partitioned design space and response correction techniques for design refinement. Demonstra
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Comparison of image pre-processing methods in liver segmentation task
PublikacjaAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review
PublikacjaThe segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...
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DentalSegmentator: robust deep learning-based CBCT image segmentation
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Automatic evaluation of information credibility in Semantic Web and Knowledge Grid
PublikacjaThis article presents a novel algorithm for automatic estimation of information credibility. It concerns information collected in Knowledge Grid and Semantic Web. Possibilities to evaluate the credibility of information in such structures are much greater than those available for WWW sites which use natural language. The rating system presented in this paper estimates credibility automatically on the basis of the following metrics:...
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WordVenture - COOPERATIVE WordNet EDITOR Architecture for Lexical Semantic Acquisition
PublikacjaThis article presents architecture for acquiring lexical semantics in a collaborative approach paradigm. The system enables functionality for editing semantic networks in a wikipedia-like style. The core of the system is a user-friendly interface based on interactive graph navigation. It has been used for semantic network presentation, and brings simultaneously modification functionality.
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Colour Terms in Five Linguistic Images of the World: The Semantic Perspective
PublikacjaSocial and cultural factors shape the linguistic perception of colour. At the same time, colour terms co-create the linguistic image of the world, which allows us to interpret reality and profile our statements and beliefs. This paper presents six basic colour terms: white, black, red, green, yellow, and blue (both as adjectives and as nouns) in the five different linguistic images of the world of the following languages: English,...
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A Hyperdense Semantic Domain for Discontinuous Behavior in Physical System Models
PublikacjaMultiple time models have been proposed for the formalization of hybrid dynamic system behavior. The superdense notion of time is a well-known time model for describing event-based systems where several events can occur simultaneously. Hyperreals provide a domain for defining the semantics of hybrid models that is elegantly aligned with first principles in physics. This paper discusses the value of both time models and shows how...
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A Ubiquitous System Using Semantic Knowledge in Dynamic Service Integration
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Wordventure - cooperative wordnet editor. Architecture for lexical semantic aquisition
PublikacjaThis article presents architecture for acquiring lexical semanticsin a collaborative approach paradigm. The system enablesfunctionality for editing semantic networks in a wikipedia-like style. The core of the system is a user-friendly interface based on interactive graph navigation.It has been used for semantic network presentation,and brings simultaneously modification functionality.
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Romantic Texutalities (formerly: Romantic Textualities)
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The fermentation process integrated with membrane distillation
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Universal Augmentation Schemes for Network Navigability
PublikacjaRozważano problem uzupełniania grafu (reprezentującego np. sieci społeczne) poprzez dodanie w każdym węźle jednego dodatkowego skierowanego połączenia (długodystansowego). Dokładniej, dla każdego węzła definiuje się listę prawdopodobieństw istnienia połączenia wychodzącego z danego węzła do wszystkich pozostałych węzłów; wartości tych prawdopodobieństw muszą sumować się do jedności. Routing zachłanny w takiej sieci polega na przekazywaniu...
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Application of colour image segmentation for localization and extraction text from images
PublikacjaW otaczającym nas świecie informacja tekstowa odgrywa wielką rolę. W postaci tekstowej podawane są: nazwy ulic, nazwy sklepów i instytucji, opisy przedmiotów np. tytuły książek, opakowań itp. Jednocześnie współczesne programy komputerowe służące do rozpoznawania tekstu (OCR) ''nie radzą sobie'' z analizą obrazów otrzymanaych za pomocą kamer. Segmentacja obrazu z następującą kontekstową analizą parametrów segmentów może dostarczyć...
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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublikacjaIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Modeling the Customer’s Contextual Expectations Based on Latent Semantic Analysis Algorithms
PublikacjaNowadays, in the age of Internet, access to open data detects the huge possibilities for information retrieval. More and more often we hear about the concept of open data which is unrestricted access, in addition to reuse and analysis by external institutions, organizations and people. It’s such information that can be freely processed, add another data (so-called remix) and then published. More and more data are available in text...
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Improving the Accuracy in Sentiment Classification in the Light of Modelling the Latent Semantic Relations
PublikacjaThe research presents the methodology of improving the accuracy in sentiment classification in the light of modelling the latent semantic relations (LSR). The objective of this methodology is to find ways of eliminating the limitations of the discriminant and probabilistic methods for LSR revealing and customizing the sentiment classification process (SCP) to the more accurate recognition of text tonality. This objective was achieved...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublikacjaBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublikacjaAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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KEMR-Net: A Knowledge-Enhanced Mask Refinement Network for Chromosome Instance Segmentation
PublikacjaThis article proposes a mask refinement method for chromosome instance segmentation. The proposed method exploits the knowledge representation capability of Neural Knowledge DNA (NK-DNA) to capture the semantics of the chromosome’s shape, texture, and key points, and then it uses the captured knowledge to improve the accuracy and smoothness of the masks. We validate the method’s effectiveness on our latest high-resolution chromosome...
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Segmentation-Based BI-RADS Ensemble Classification of Breast Tumours in Ultrasound Images
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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublikacjaMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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Heat transfer augmentation using liquid crystal
PublikacjaPraca przedstawia zastosowanie techniki wizualizacji ciekłokrystalicznej dobadań wymiany ciepła na płaskiej powierzchni z zaburzaczami. Folia ciekło-krystaliczna została umieszczona na powierzchni, aby określić przebieg izoterm. Obraz rejestrowano kamerą JVC, a następnie analizowano komputerowo. Procedura eksperymentalna pozwala na otrzymanie pełnej informacji dotyczącej wymiany ciepła (na powierzchni płaskiej z elementami ustawionymi...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublikacjaThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Pretreatment of Lignocellulosic Materials as Substrates for Fermentation Processes
PublikacjaLignocellulosic biomass is an abundant and renewable resource that potentially contains large amounts of energy. It is an interesting alternative for fossil fuels, allowing the production of biofuels and other organic compounds. In this paper, a review devoted to the processing of lignocellulosic materials as substrates for fermentation processes is presented. The review focuses on physical, chemical, physicochemical, enzymatic,...
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Toward Robust Pedestrian Detection With Data Augmentation
PublikacjaIn this article, the problem of creating a safe pedestrian detection model that can operate in the real world is tackled. While recent advances have led to significantly improved detection accuracy on various benchmarks, existing deep learning models are vulnerable to invisible to the human eye changes in the input image which raises concerns about its safety. A popular and simple technique for improving robustness is using data...
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Modelling of dark fermentation of glucose and sour cabbage
PublikacjaIn the article, modified Anaerobic Digestion Models 1 (ADM-1) was tested for modelling dark fermentation for hydrogen production. The model refitting was done with the Euler method. The new model was based on sets of differential equations. The model was checked for hydrogen production from sour cabbage in batch and semi-batch in 5 g VSS (volatile solid suspension)/L and at the semi-batch process from glucose at 5 and 10 g VSS/L....