Wyniki wyszukiwania dla: SEMANTIC KNOWLEDGE - MOST Wiedzy

Wyszukiwarka

Wyniki wyszukiwania dla: SEMANTIC KNOWLEDGE

Filtry

wszystkich: 124
wybranych: 112

wyczyść wszystkie filtry


Filtry wybranego katalogu

  • Kategoria

  • Rok

  • Opcje

wyczyść Filtry wybranego katalogu niedostępne

Wyniki wyszukiwania dla: SEMANTIC KNOWLEDGE

  • Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2024

    This guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...

    Pełny tekst do pobrania w portalu

  • Semantic segmentation training using imperfect annotations and loss masking

    One of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Robust Object Detection with Multi-input Multi-output Faster R-CNN

    Publikacja

    Recent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Robust Object Detection with Multi-input Multi-output Faster R-CNN

    Publikacja

    Recent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...

    Pełny tekst do pobrania w portalu

  • Asking Data in a Controlled Way with Ask Data Anything NQL

    Publikacja
    • A. Seganti
    • P. Kapłański
    • J. Campo
    • K. Cieśliński
    • J. Koziołkiewicz
    • P. Zarzycki

    - Rok 2016

    While to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Urban scene semantic segmentation using the U-Net model

    Publikacja

    - Rok 2023

    Vision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...

    Pełny tekst do pobrania w serwisie zewnętrznym

  • Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift

    While recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...

    Pełny tekst do pobrania w portalu

  • Techniki modularyzacji ontologii

    Publikacja

    W ciągu ostatnich kilku lat tematem wielu prac naukowych stała się modularyzacja ontologii. Istnieje kilka przyczyn dużego zainteresowania tym kierunkiem prac. Z jednej strony ontologie wykazały swoją przydatność w różnego rodzaju przedsięwzięciach związanych z inicjatywą Semantic Web. Z drugiej strony okazało się, że po przekroczeniu pewnej granicy wielkości ontologii inżynierowie wiedzy natykają się na problemy, z którymi inżynieria...

  • Distributed Architectures for Intensive Urban Computing: A Case Study on Smart Lighting for Sustainable Cities

    Publikacja

    - IEEE Access - Rok 2019

    New information and communication technologies have contributed to the development of the smart city concept. On a physical level, this paradigm is characterised by deploying a substantial number of different devices that can sense their surroundings and generate a large amount of data. The most typical case is image and video acquisition sensors. Recently, these types of sensors are found in abundance in urban spaces and are responsible...

    Pełny tekst do pobrania w portalu

  • Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis

    Most of the research in the field of emotion recognition is based on datasets that contain data obtained during affective computing experiments. However, each dataset is described by different metadata, stored in various structures and formats. This research can be counted among those whose aim is to provide a structural and semantic pattern for affective computing datasets, which is an important step to solve the problem of data...

    Pełny tekst do pobrania w portalu

  • Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network

    To effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...

    Pełny tekst do pobrania w portalu

  • Identification of category associations using a multilabel classifier

    Description of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...

    Pełny tekst do pobrania w serwisie zewnętrznym