Otsing - TalTech Publikatsioonid

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A machine learning approach to achieving energy efficiency in relay-assisted LTE-a downlink systemHassan, Hammad; Ahmed, Ifran; Ahmad, Rizwan; Khammari, Hedi; Bhatti, Ghulam; Ahmed, Waqas; Alam, Muhammad MahtabSensors2019 / art. 3461, 25 p. : ill https://doi.org/10.3390/s19163461

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A novel short receptive field based dilated causal convolutional network integrated with Bidirectional LSTM for short-term load forecastingJaved, Umar; Ijaz, Khalid; Jawad, Muhammad; Khosa, Ikramullah; Ansari, Ejaz Ahmad; Zaidi, Khurram Shabih; Rafiq, Muhammad Nadeem; Shabbir, NomanExpert systems with applications2022 / art. 117689 https://doi.org/10.1016/j.eswa.2022.117689

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A systematic literature review of AI-based digital decision support systems for post-traumatic stress disorderBertl, Markus; Metsallik, Janek; Ross, PeeterFrontiers in Psychiatry2022 https://doi.org/10.3389/fpsyt.2022.923613

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Accuracy analysis of selected time series and machine learning methods for smart cities based on Estonian electricity consumption forecastHäring, Tobias; Ahmadiahangar, Roya; Rosin, Argo; Korõtko, Tarmo; Biechl, Helmuth2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG) : proceedings2020 / p. 425-428 : ill https://doi.org/10.1109/CPE-POWERENG48600.2020.9161690

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Applicability of spiral drawing test for mental fatigue modellingSenkiv, Olesja; Nõmm, Sven; Toomela, AaroIFAC-PapersOnLine2019 / p. 190-195 : ill https://doi.org/10.1016/j.ifacol.2019.01.064

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Application of machine learning for assessment of HS code correctnessSpitšakova, Margarita; Haav, Hele-MaiBaltic journal of modern computing2020 / p. 698-718 https://doi.org/10.22364/bjmc.2020.8.4.13

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Applying machine learning with satellite altimetry data for prediction of absolute dynamic topography for the Baltic SeaMostafavi, Majid; Delpeche-Ellmann, Nicole Camille; Ellmann, ArtuNordic Geodetic Commission General Assembly 2022 in Copenhagen : Poster Session2022 / 26 l. https://medialib.cmcdn.dk/medialibrary/010C1367-E991-4A33-AB10-1953247E9C23/530AEABD-3A25-ED11-84B6-00155D0B0940.pdf

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Artificial intelligence and educationJaakkola, Hannu; Henno, Jaak; Lahti, J-P.; Järvinen, Raimo; Mäkelainen, Jukka2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 28 Sept.-2 Oct. 2020, Opatija, Croatia : proceedings2020 / p. 548-555 https://doi.org/10.23919/MIPRO48935.2020.9245329

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Artificial intelligence and the GDPR : Inevitable nemeses?Kesa, Aleksandr; Kerikmäe, TanelTalTech journal of European studies2020 / p. 68-90 https://doi.org/10.1515/bjes-2020-0022 https://content.sciendo.com/view/journals/bjes/bjes-overview.xml?tab_body=latestIssueToc-79907 https://www.ester.ee/record=b5290032*est

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Artificial intelligence in monitoring and diagnostics of electrical energy conversion systemsVaimann, Toomas; Rassõlkin, Anton; Kallaste, Ants; Pomarnacki, Raimondas; Belahcen, Anouar; Van Khang, Hyunh2020 27th International Workshop on Electric Drives: MPEI Department of Electric Drives 90th Anniversary (IWED), Moscow, Russia, January 27-30, 20202020 / 4 p https://doi.org/10.1109/IWED48848.2020.9069566

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Artificial intelligence within the military domain and cyber warfareHallaq, Bil; Sõmer, Tiia; Osula, Anna-Maria; Ngo, Kim; Mitchener-Nissen, TimothyProceedings of the 16th European Conference on Cyber Warfare and Security, ECCWS 2017 : hosted by University College Dublin, Ireland, 29-30 June 20172017 / p. 153-156 https://www.scopus.com/record/display.uri?eid=2-s2.0-85028013021&origin=resultslist&zone=contextBox

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Artificial lateral line for aquatic habitat modelling: An example for Lefua echigoniaGarcia-Vega, Ana; Fuentes-Perez, Juan Francisco; Fukuda, Shinji; Kruusmaa, Maarja; Sanz-Ronda, Francisco Javier; Tuhtan, Jeffrey AndrewEcological Informatics2021 / art. 101388 https://doi.org/10.1016/j.ecoinf.2021.101388

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CapsNet on embedded devices in a data scarce scenarioEzechukwu, Dismas Ndubuis; Le Moullec, Yannick2022 18th Biennial Baltic Electronics Conference (BEC)2022 / 6 l. https://doi.org/10.1109/BEC56180.2022.9935600

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Comparison of machine learning based methods for residential load forecastingShabbir, Noman; Ahmadiahangar, Roya; Kütt, Lauri; Rosin, Argo2019 Electric Power Quality and Supply Reliability Conference (PQ) & 2019 Symposium on Electrical Engineering and Mechatronics (SEEM), Kärdla, Estonia, June 12-15, 2019 : proceedings2019 / 4 p. : ill https://doi.org/10.1109/PQ.2019.8818267

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Custom simplified machine learning algorithms for fault diagnosis in electrical machinesRaja, Hadi Ashraf; Asad, Bilal; Vaimann, Toomas; Kallaste, Ants; Rassõlkin, Anton; Belahcen, AnouarDiagnostika '22 : 2022 International Conference on Diagnostics in Electrical Engineering : Conference proceedings2022 / 4 p. https://doi.org/10.1109/Diagnostika55131.2022.9905174

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Detailed analysis of the Luria's alternating series tests for Parkinson's disease diagnosticsNõmm, Sven; Bardõš, Konstantin; Toomela, Aaro; Medijainen, Kadri; Taba, Pille17th IEEE International Conference on Machine Learning and Applications : ICMLA 2018, 17–20 December 2018, Orlando, Florida, USA : proceedings2018 / p. 1347–1352 https://doi.org/10.1109/ICMLA.2018.00219

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Detecting Simpson’s paradox : a machine learning perspectiveSharma, Rahul; Garayev, Huseyn; Kaushik, Minakshi; Arakkal Peious, Sijo; Tiwari,Prauag; Draheim, DirkDatabase and Expert Systems Applications : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022 : proceedings, Part I2022 / p. 323-335 : ill https://doi.org/10.1007/978-3-031-12423-5_25

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Detecting Simpson’s paradox : a step towards fairness in machine learningSharma, Rahul; Kaushik, Minakshi; Arakkal Peious, Sijo; Markus, Bertl; Ankit, Vidyarthi; Ashwani, Kumar; Draheim, DirkNew Trends in Database and Information Systems : ADBIS 2022 Short Papers, Doctoral Consortium and Workshops : DOING, K-GALS, MADEISD, MegaData, SWODCH, Turin, Italy, September 5–8, 2022 : proceedings2022 / p. 67-76 : ill https://doi.org/10.1007/978-3-031-15743-1_7

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Detection of bulbar involvement in patients with amyotrophic lateral sclerosis by machine learning voice analysis : diagnostic decision support development studyTena, Alberto; Claria, Francec; Solsona, Francesc; Meister, Einar; Povedano, MonicaJMIR Medical Informatics2021 / e21331, 18 p. : ill https://doi.org/10.2196/21331

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Differences in android behavior between real device and emulator : a malware detection perspectiveGuerra Manzanares, Alejandro; Bahsi, Hayretdin; Nõmm, Sven6th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), Granada, Spain, October 22-25, 20192019 / art. 8939268, p. 399-404 https://doi.org/10.1109/IOTSMS48152.2019.8939268

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Dimensionality reduction for machine learning based IoT botnet detectionBahsi, Hayretdin; Nõmm, Sven15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018) : Singapore, November 18-21, 20182018 / p. 1857-1862 : ill https://doi.org/10.1109/ICARCV.2018.8581205

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Discretizing numerical attributes : an analysis of human perceptionsKaushik, Minakshi; Sharma, Rahul; Vidyarthi, Ankit; Draheim, DirkNew Trends in Database and Information Systems : ADBIS 2022 Short Papers, Doctoral Consortium and Workshops : DOING, K-GALS, MADEISD, MegaData, SWODCH, Turin, Italy, September 5–8, 2022 : Proceedings2022 / p. 188-197 https://doi.org/10.1007/978-3-031-15743-1_18

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Driver distraction detection and evaluation with artificial neural network and fuzzy logic : In-vehicle information system as a driver's secondary activity: case studyAksjonov, Andrei; Nedoma, Pavel; Vodovozov, Valery; Petlenkov, Eduard15th International Workshop on Advanced Motion Control : (AMC 2018), Tokyo, Japan2018 / p. 523–528 : ill https://www.researchgate.net/publication/323747995_Driver_Distraction_Detection_and_Evaluation_with_Artificial_Neural_Network_and_Fuzzy_Logic_In-vehicle_information_system_as_a_driver%27s_secondary_activity_Case_study

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Enabling cross-layer reliability and functional safety assessment through ML-based compact modelsAlexandrescu, Dan; Balakrishnan, Aneesh; Lange, Thomas; Glorieux, MaximilienProceedings : 2020 26th IEEE International Symposium on On-Line Testing and Robust System Design : IOLTS 2020, Napoli, Italy, July 13-16, 2020 : virtual edition2020 / 6 p. : ill https://doi.org/10.1109/IOLTS50870.2020.9159750

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Explainability and transparency of classifiers for air-handling unit faults using explainable artificial intelligence (XAI)Meas, Molika; Machlev, Ram; Köse, Ahmet; Tepljakov, Aleksei; Loo, Lauri; Levron, Yoash; Petlenkov, Eduard; Belikov, JuriSensors2022 / art. 6338 : ill http://doi.org/10.3390/s22176338

artikkel ajakirjas

machine learning (võtmesõna)

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