Temat: feature context - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Signature verification using contextual information enhancement and dynamic programming
Autorzy:: Adamski, M.
Saeed, K.
Powiązania:: https://bibliotekanauki.pl/articles/332874.pdf
Data publikacji:: 2008
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: weryfikacja podpisu online
programowanie dynamiczne
online signature verification
feature context
dynamic programming
Opis:: This paper presents the results of experiments on online signature verification. Information gathered during the signing process like pen trajectory, pressure, elevation and altitude is utilized to prove the authenticity of a signature or to detect a forgery attempt. Signature verification task is carried out by means of the Template Matching approach. The presented method is based on the signature description in terms of its local features and their relations. The comparison of features in the reference and tested signatures is conducted using Dynamic Time Warping technique.
Źródło:: Journal of Medical Informatics & Technologies; 2008, 12; 35-40
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: The prediction of the low fetal birth weight based on quantitative description of cardiotocographic signals
Autorzy:: Czabański, R.
Jeżewski, M.
Wróbel, J.
Kupka, T.
Łęski, J.
Jeżewski, J.
Powiązania:: https://bibliotekanauki.pl/articles/333495.pdf
Data publikacji:: 2008
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: weryfikacja podpisu online
programowanie dynamiczne
online signature verification
feature context
dynamic programming
Opis:: Cardiotocography (CTG) is a routine method of fetal condition assessment used in modern obstetrics. It is a biophysical method based on simultaneous recording and analysis of activity of fetal heart, fetal movements and maternal uterine contractions. The fetal condition is diagnosed on the basis of printed CTG trace evaluation. The correct interpretation of CTG traces from a bedside monitor is very difficult even for experienced clinicians. Therefore, computerized fetal monitoring systems are used to yield the quantitative description of the signal. However, the effective methods, aiming to support the conclusion generation, are still being searched. One of the most important features defining the state of fetal outcome is the weight of the newborn. The presented work describes an application of the Artificial Neural Network Based on Logical Interpretation of fuzzy if-then Rules (ANBLIR) to evaluate the risk of the low birth weight using a set of parameters quantitatively describing the CTG traces. The obtained results confirm that the neuro-fuzzy based CTG classification methods are very efficient for the prediction of the fetal outcome.
Źródło:: Journal of Medical Informatics & Technologies; 2008, 12; 97-102
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Named-entity recognition for Hindi language using context pattern-based maximum entropy
Autorzy:: Jain, Arti
Yadav, Divakar
Arora, Anuja
Tayal, Devendra K.
Powiązania:: https://bibliotekanauki.pl/articles/27312839.pdf
Data publikacji:: 2022
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: context patterns
gazetteer lists
Hindi language
Kaggle dataset
maximum entropy
named-entity recognition
feature extension
Opis:: This paper describes a named-entity-recognition (NER) system for the Hindi language that uses two methodologies: an existing baseline maximum entropy-based named-entity (BL-MENE) model, and the proposed context pattern-based MENE (CP-MENE) framework. BL-MENE utilizes several baseline features for the NER task but suffers from inaccurate named-entity (NE) boundary detection, misclassification errors, and the partial recognition of NEs due to certain missing essentials. However, the CP-MENE-based NER task incorporates extensive features and patterns that are set to overcome these problems. In fact, CP-MENE’s features include right-boundary, left-boundary, part-of-speech, synonym, gazetteer and relative pronoun features. CP-MENE formulates a kind of recursive relationship for extracting highly ranked NE patterns that are generated through regular expressions via Python@ code. Since the web content of the Hindi language is arising nowadays (especially in health care applications), this work is conducted on the Hindi health data (HHD) corpus (which is readily available from the Kaggle dataset). Our experiments were conducted on four NE categories; namely, Person (PER), Disease (DIS), Consumable (CNS), and Symptom (SMP).
Źródło:: Computer Science; 2022, 23 (1); 81--115
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

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