Identification of G protein-coupled receptors in Schistosoma haematobium and S. mansoni by comparative genomics

Autor: Tulio D L Campos, Neil D Young, Pasi K Korhonen, Ross S Hall, Stefano Mangiola, Andrew Lonie, Robin B Gasser

Publikováno v: Parasites & Vectors, Vol 7, Iss 1, Pp 1-11 (2014)

Abstract Background Schistosomiasis is a parasitic disease affecting ~200 million people worldwide. Schistosoma haematobium and S. mansoni are two relatively closely related schistosomes (blood flukes), and the causative agents of urogenital and hepa

Externí odkaz: https://doaj.org/article/5461995a63514e26b818489d4502e6ee

Parallel Prefiltering for Accelerating HHblits on the Convey HC-1

Autor: Fabian Nowak, Michael Bromberger

Publikováno v: PARS-Mitteilungen. 30:47-57

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::71545880a3eb23d9317ea5bd02b6945b
https://doi.org/10.1007/bf03354237

Using Wikipedia for Cross-Language Named Entity Recognition

Autor: Fernandes, Eraldo R., Brefeld, Ulf, Blanco, Roi, Atserias, Jordi

Publikováno v: Fernandes, E R, Brefeld, U, Blanco, R & Atserias, J 2016, Using Wikipedia for Cross-Language Named Entity Recognition . in M Atzmüller, A Chin, F Janssen, I Schweizer & C Trattner (eds), Big Data Analytics in the Social and Ubiquitous Context : 5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9546, Springer International Publishing AG, pp. 1-25, 5th International Workshop on Mining Ubiquitous and Social Environments-MUSE 2014, Nancy, France, 15.09.14 . https://doi.org/10.1007/978-3-319-29009-6_1
Fernandes, E R, Brefeld, U, Blanco, R & Atserias, J 2016, Using Wikipedia for Cross-Language Named Entity Recognition . in M Atzmüller, A Chin, F Janssen, I Schweizer & C Trattner (eds), Big Data Analytics in the Social and Ubiquitous Context : 5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers . Lecture Notes in Computer Science, no. 9546, Springer International Publishing AG, pp. 1-25, 5th International Workshop on Mining Ubiquitous and Social Environments-MUSE 2014, Nancy, France, 15.09.14 . DOI: 10.1007/978-3-319-29009-6_1

Named entity recognition and classification (NERC) is fundamental for natural language processing tasks such as information extraction, question answering, and topic detection. State-of-the-art NERC systems are based on supervised machine learning an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::462aab3f1b8ec7fe961a684ba322dac4
http://fox.leuphana.de/portal/de/publications/using-wikipedia-for-crosslanguage-named-entity-recognition(6e4b3c84-7912-49f2-ad0e-98fd7e464d1c).html

Automatic Detection of Deviations in Human Movements Using HMM: Discrete vs Continuous

Autor: Carlos Palma, Augusto Salazar, Francisco Vargas

Publikováno v: Advances in Visual Computing ISBN: 9783319508313
ISVC (2)

Automatic detection of correct performance of movements in humans is the core of coaching and rehabilitation applications. Human movement can be studied in terms of sequential data by using different sensor technologies. This representation makes it

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::81d7635e900b3f655b14953efedf6739
https://doi.org/10.1007/978-3-319-50832-0_52

A Hybrid CRF/HMM for One-Shot Gesture Learning

Autor: Clément Chatelain, Selma Belgacem, Thierry Paquet

Publikováno v: Adaptive Biometric Systems: Recent Advances and Challenges
Ajita Rattani; Fabio Roli; Eric Granger. Adaptive Biometric Systems: Recent Advances and Challenges, Springer, pp.51-72, 2015, 978-3-319-24865-3. ⟨10.1007/978-3-319-24865-3_4⟩
Adaptive Biometric Systems ISBN: 9783319248639

International audience; This chapter deals with the characterization and the recognition of human gestures in videos. We propose a global characterization of gestures that we call the Gesture Signature. The gesture signature describes the location, v

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de3ad74032c30fa1dd32f51a8988f0a3
https://normandie-univ.hal.science/hal-02075745