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1
artikkel kogumikus
Accuracy analysis of selected time series and machine learning methods for smart cities based on Estonian electricity consumption forecast
Häring, Tobias
;
Ahmadiahangar, Roya
;
Rosin, Argo
;
Korõtko, Tarmo
;
Biechl, Helmuth
2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG) : proceedings
2020
/
p. 425-428 : ill
https://doi.org/10.1109/CPE-POWERENG48600.2020.9161690
artikkel kogumikus
2
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Applicability of spiral drawing test for mental fatigue modelling
Senkiv, Olesja
;
Nõmm, Sven
;
Toomela, Aaro
IFAC-PapersOnLine
2019
/
p. 190-195 : ill
https://doi.org/10.1016/j.ifacol.2019.01.064
Conference proceedings at Scopus
Article at Scopus
Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
3
artikkel ajakirjas
Application of artificial intelligence and machine learning for BIM : review
Bassir, David
;
Lodge, Hugo
;
Chang, Haochen
;
Majak, Jüri
;
Chen, Gonfa
International journal for simulation and multidisciplinary design optimization
2023
/
art. 5
https://doi.org/10.1051/smdo/2023005
artikkel ajakirjas
4
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Application of machine learning for assessment of HS code correctness
Spitšakova, Margarita
;
Haav, Hele-Mai
Baltic journal of modern computing
2020
/
p. 698-718
https://doi.org/10.22364/bjmc.2020.8.4.13
Journal Metrics at Scopus
Article at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
5
artikkel kogumikus
Applying machine learning with satellite altimetry data for prediction of absolute dynamic topography for the Baltic Sea
Mostafavi, Majid
;
Delpeche-Ellmann, Nicole Camille
;
Ellmann, Artu
Nordic Geodetic Commission General Assembly 2022 in Copenhagen : Poster Session
2022
/
26 l.
https://medialib.cmcdn.dk/medialibrary/010C1367-E991-4A33-AB10-1953247E9C23/530AEABD-3A25-ED11-84B6-00155D0B0940.pdf
artikkel kogumikus
6
artikkel kogumikus
Artificial intelligence and education
Jaakkola, Hannu
;
Henno, Jaak
;
Lahti, J-P.
;
Järvinen, Raimo
;
Mäkelainen, Jukka
2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), 28 Sept.-2 Oct. 2020, Opatija, Croatia : proceedings
2020
/
p. 548-555
https://doi.org/10.23919/MIPRO48935.2020.9245329
artikkel kogumikus
7
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Artificial intelligence and the GDPR : Inevitable nemeses?
Kesa, Aleksandr
;
Kerikmäe, Tanel
TalTech journal of European studies
2020
/
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
Journal metrics at Scopus
Article at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
8
artikkel kogumikus
Artificial intelligence in monitoring and diagnostics of electrical energy conversion systems
Vaimann, Toomas
;
Rassõlkin, Anton
;
Kallaste, Ants
;
Pomarnacki, Raimondas
;
Belahcen, Anouar
;
Van Khang, Hyunh
2020 27th International Workshop on Electric Drives: MPEI Department of Electric Drives 90th Anniversary (IWED), Moscow, Russia, January 27-30, 2020
2020
/
4 p
https://doi.org/10.1109/IWED48848.2020.9069566
artikkel kogumikus
9
artikkel kogumikus
Artificial intelligence within the military domain and cyber warfare
Hallaq, Bil
;
Sõmer, Tiia
;
Osula, Anna-Maria
;
Ngo, Kim
;
Mitchener-Nissen, Timothy
Proceedings of the 16th European Conference on Cyber Warfare and Security, ECCWS 2017 : hosted by University College Dublin, Ireland, 29-30 June 2017
2017
/
p. 153-156
https://www.scopus.com/record/display.uri?eid=2-s2.0-85028013021&origin=resultslist&zone=contextBox
artikkel kogumikus
10
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Artificial lateral line for aquatic habitat modelling: An example for Lefua echigonia
Garcia-Vega, Ana
;
Fuentes-Perez, Juan Francisco
;
Fukuda, Shinji
;
Kruusmaa, Maarja
;
Sanz-Ronda, Francisco Javier
;
Tuhtan, Jeffrey Andrew
Ecological Informatics
2021
/
art. 101388
https://doi.org/10.1016/j.ecoinf.2021.101388
Journal metrics at Scopus
Article at Scopus
Journal metrics at WOS
Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
11
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Behavioural compass : animal behaviour recognition using magnetometers
Chakravarty, Pritish
;
Maalberg, Maiki
;
Cozzi, Gabriele
;
Ozgul, Arpat
;
Aminian, Kamiar
Movement Ecology
2019
/
Art. nr. 28
https://doi.org/10.1186/s40462-019-0172-6
Journal metrics at Scopus
Article at Scopus
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Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
12
artikkel kogumikus
CapsNet on embedded devices in a data scarce scenario
Ezechukwu, Dismas Ndubuis
;
Le Moullec, Yannick
2022 18th Biennial Baltic Electronics Conference (BEC)
2022
/
6 l.
https://doi.org/10.1109/BEC56180.2022.9935600
artikkel kogumikus
13
artikkel kogumikus
Comparison of machine learning based methods for residential load forecasting
Shabbir, Noman
;
Ahmadiahangar, Roya
;
Kütt, Lauri
;
Rosin, Argo
2019 Electric Power Quality and Supply Reliability Conference (PQ) & 2019 Symposium on Electrical Engineering and Mechatronics (SEEM), Kärdla, Estonia, June 12-15, 2019 : proceedings
2019
/
4 p. : ill
https://doi.org/10.1109/PQ.2019.8818267
artikkel kogumikus
14
artikkel kogumikus
Custom simplified machine learning algorithms for fault diagnosis in electrical machines
Raja, Hadi Ashraf
;
Asad, Bilal
;
Vaimann, Toomas
;
Kallaste, Ants
;
Rassõlkin, Anton
;
Belahcen, Anouar
Diagnostika '22 : 2022 International Conference on Diagnostics in Electrical Engineering : Conference proceedings
2022
/
4 p.
https://doi.org/10.1109/Diagnostika55131.2022.9905174
artikkel kogumikus
Seotud publikatsioonid
1
IoT based tools and methods for electrical machine diagnostics = Asjade interneti põhised tööriistad ja meetodid elektrimasinate diagnostikaks
15
artikkel kogumikus
Data science-based techniques for modelling and diagnostics of battery cells based on end-of-life criteria
Gilbert Zequera, Rolando Antonio
;
Rassõlkin, Anton
;
Vaimann, Toomas
;
Kallaste, Ants
2023 International Conference on Electrical Drives and Power Electronics (EDPE)
2023
/
6 p
https://doi.org/10.1109/EDPE58625.2023.10274007
artikkel kogumikus
16
artikkel kogumikus
Detailed analysis of the Luria's alternating series tests for Parkinson's disease diagnostics
Nõmm, Sven
;
Bardõš, Konstantin
;
Toomela, Aaro
;
Medijainen, Kadri
;
Taba, Pille
17th IEEE International Conference on Machine Learning and Applications : ICMLA 2018, 17–20 December 2018, Orlando, Florida, USA : proceedings
2018
/
p. 1347–1352
https://doi.org/10.1109/ICMLA.2018.00219
artikkel kogumikus
17
artikkel kogumikus EST
/
artikkel kogumikus ENG
Detecting Simpson’s paradox : a machine learning perspective
Sharma, Rahul
;
Garayev, Huseyn
;
Kaushik, Minakshi
;
Arakkal Peious, Sijo
;
Tiwari,Prauag
;
Draheim, Dirk
Database and Expert Systems Applications : 33rd International Conference, DEXA 2022, Vienna, Austria, August 22-24, 2022 : proceedings. Part I
2022
/
p. 323-335 : ill
https://doi.org/10.1007/978-3-031-12423-5_25
Conference Proceedings at Scopus
Article at Scopus
Conference Proceedings at WOS
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Unification of decision support techniques : mitigating statistical paradoxes for enabling trustworthy decision making = Otsuste toetamise tehnikate ühtlustamine : statistiliste paradokside mõju maandamine usaldusväärsete otsuste tegemise võimaldamiseks
18
artikkel kogumikus EST
/
artikkel kogumikus ENG
Detecting Simpson’s paradox : a step towards fairness in machine learning
Sharma, Rahul
;
Kaushik, Minakshi
;
Arakkal Peious, Sijo
;
Bertl, Markus
;
Ankit, Vidyarthi
;
Ashwani, Kumar
;
Draheim, Dirk
New 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 : proceedings
2022
/
p. 67-76 : ill
https://doi.org/10.1007/978-3-031-15743-1_7
Conference proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Unification of decision support techniques : mitigating statistical paradoxes for enabling trustworthy decision making = Otsuste toetamise tehnikate ühtlustamine : statistiliste paradokside mõju maandamine usaldusväärsete otsuste tegemise võimaldamiseks
19
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Detection and evaluation of driver distraction using machine learning and fuzzy logic
Aksjonov, Andrei
;
Nedoma, Pavel
;
Vodovozov, Valery
;
Petlenkov, Eduard
;
Herrmann, Martin
IEEE Transactions on Intelligent Transportation Systems
2019
/
p. 2048 - 2059
https://doi.org/10.1109/TITS.2018.2857222
Journal metrics at Scopus
Article at Scopus
Journal metrics at WOS
Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
20
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Detection of bulbar involvement in patients with amyotrophic lateral sclerosis by machine learning voice analysis : diagnostic decision support development study
Tena, Alberto
;
Claria, Francec
;
Solsona, Francesc
;
Meister, Einar
;
Povedano, Monica
JMIR Medical Informatics
2021
/
e21331, 18 p. : ill
https://doi.org/10.2196/21331
Journal metrics at Scopus
Article at Scopus
Journal metrics at WOS
Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
21
artikkel kogumikus
Differences in Android behavior between real device and emulator : a malware detection perspective
Guerra Manzanares, Alejandro
;
Bahsi, Hayretdin
;
Nõmm, Sven
6th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), Granada, Spain, October 22-25, 2019
2019
/
art. 8939268, p. 399-404
https://doi.org/10.1109/IOTSMS48152.2019.8939268
artikkel kogumikus
22
artikkel kogumikus
Dimensionality reduction for machine learning based IoT botnet detection
Bahsi, Hayretdin
;
Nõmm, Sven
15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018) : Singapore, November 18-21, 2018
2018
/
p. 1857-1862 : ill
https://doi.org/10.1109/ICARCV.2018.8581205
artikkel kogumikus
23
artikkel ajakirjas
Discretizing numerical attributes : an analysis of human perceptions
Kaushik, Minakshi
;
Sharma, Rahul
;
Draheim, Dirk
arXiv.org
2023
/
18 p. : ill
https://doi.org/10.48550/arXiv.2311.03278
artikkel ajakirjas
Seotud publikatsioonid
1
Generalized association rule mining – dimensional unsupervised learning = Üldistatud assotsiatsioonireeglite kaevandamine – dimensiooniline juhendamata õpe
24
artikkel kogumikus EST
/
artikkel kogumikus ENG
Discretizing numerical attributes : an analysis of human perceptions : [conference paper]
Kaushik, Minakshi
;
Sharma, Rahul
;
Vidyarthi, Ankit
;
Draheim, Dirk
New 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 : proceedings
2022
/
p. 188-197
https://doi.org/10.1007/978-3-031-15743-1_18
Conference proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Generalized association rule mining – dimensional unsupervised learning = Üldistatud assotsiatsioonireeglite kaevandamine – dimensiooniline juhendamata õpe
25
artikkel kogumikus
Driver distraction detection and evaluation with artificial neural network and fuzzy logic : In-vehicle information system as a driver's secondary activity: case study
Aksjonov, Andrei
;
Nedoma, Pavel
;
Vodovozov, Valery
;
Petlenkov, Eduard
15th International Workshop on Advanced Motion Control : (AMC 2018), Tokyo, Japan
2018
/
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
artikkel kogumikus
Kirjeid leitud 99, kuvan
1 - 25
eelmine
1
2
3
4
järgmine
võtmesõna
268
1.
adversarial machine learning
2.
adversarial machine-learning
3.
automatic machine learning (autoML)
4.
machine learning
5.
machine learning (ML)
6.
machine learning algorithms
7.
machine learning approach
8.
Machine Learning Explainable model
9.
machine learning for environmental applications
10.
machine-learning predictive model
11.
Parkinson’s disease machine learning
12.
robust machine learning
13.
small data machine learning
14.
supervised machine learning
15.
unsupervised machine learning
16.
machine-to-machine communications
17.
AC machine
18.
Algorithmic State Machine - ASM
19.
axial flux machine
20.
axial flux switched reluctance machine
21.
bearingless machine
22.
brushless machine
23.
coordinate measurring machine
24.
electric machine
25.
electric machine analysis computing
26.
electric machine control
27.
electrical machine
28.
electrical machine cooling
29.
electrical machine design
30.
finite state machine
31.
Finite State Machine - FSM
32.
hierarchical finite state machine
33.
human machine interaction
34.
human machine systems
35.
human-machine interaction
36.
human-machine interface
37.
human-machine system
38.
induction machine
39.
interior permanent magnet machine
40.
interior permanent-magnet synchronous machine (IPMSM)
41.
linear machine
42.
machine bearings
43.
machine condition monitoring
44.
machine control
45.
machine design
46.
machine elements
47.
machine error
48.
machine housing
49.
machine tools
50.
machine vector control
51.
machine windings
52.
machine vision
53.
machine-translation
54.
man-machine systems
55.
massive machine-type communication (mMTC)
56.
massive machine-type communications (mMTC)
57.
massive Machine-Type connections (mMTC)
58.
multi-class support vector machine (m-SVM)
59.
multi-machine
60.
multi-machine industrial power plant
61.
multi-machine power system
62.
multi-stream interaction machine
63.
outer-rotor machine
64.
permanent magnet (PM) synchronous machine
65.
permanent magnet flux-switching machine
66.
permanent magnet machine
67.
permanent magnet synchronous machine (PMSM)
68.
sewing machine operator
69.
state machine
70.
support vector machine
71.
surface permanent magnet machine (SPM)
72.
switched reluctance machine
73.
switched reluctance machine (SRM)
74.
synchronous machine
75.
TBM (tunnel boring machine)
76.
totally enclosed fan-cooled machine
77.
universal friction machine
78.
virtual synchronous machine
79.
active learning
80.
active learning methods
81.
algorithm controlling the learning process
82.
appetitive associative learning
83.
approach to learning
84.
Attitude to learning
85.
authoritarian learning
86.
automata learning
87.
BIM-enabled learning
88.
BIM-enabled learning environment
89.
blended learning
90.
business school as learning organization
91.
business school learning organization questionnaire (BSLOQ)
92.
business school learning rate dependence on GPD
93.
business school learning rate measurement instrument
94.
client learning
95.
Collaborative e-learning
96.
collaborative learning
97.
competence based learning
98.
competence learning
99.
competence-based learning
100.
competency based learning
101.
Component organised learning (COL)
102.
computer assisted language learning
103.
computer based learning
104.
computer-assisted language learning (CALL)
105.
cooperative reinforcement learning
106.
coping with online teaching and learning
107.
customer learning
108.
deep learning
109.
deep learning (DL)
110.
deep learning classifier
111.
deep learning model
112.
deep learning network
113.
deep reinforcement learning
114.
Deep reinforcing learning SDN
115.
Deep-learning
116.
deep-learning (DL)
117.
dictionary learning
118.
digital learning module
119.
Dimensions of Learning Organisation Questionnaire (DLOQ)
120.
distance learning
121.
distant learning
122.
distributed independent reinforcement learning
123.
double Q-learning
124.
effective teaching and learning
125.
e-learning
126.
e‐learning
127.
e-Learning course
128.
e-Learning database
129.
e-learning environment
130.
electronic learning
131.
embedded deep learning
132.
Emergency remote learning
133.
ensemble learning
134.
enterprising and entrepreneurial learning
135.
entrepreneurial learning
136.
entrepreneurial teaching and learning
137.
experiential learning
138.
Federated learning
139.
federated learning (FL)
140.
flexible learning
141.
game based learning
142.
game-based learning
143.
guided in-service learning
144.
hands-on-learning
145.
history learning
146.
hybrid learning
147.
incremental learning
148.
inductive learning
149.
inductive learning algorithm
150.
interactive learning objects
151.
interdisciplinary learning
152.
inverse reinforcement learning
153.
investor learning
154.
iterative learning
155.
Learner-centered learning environment
156.
learning
157.
learning (artificial intelligence)
158.
learning activities
159.
learning adaptation in autonomous vehicles
160.
learning algorithm
161.
learning analysis
162.
learning analytics
163.
learning and experimentation
164.
learning and health outcomes
165.
learning and memory
166.
learning business school
167.
learning by teaching
168.
learning concept
169.
learning difficulties
170.
Learning environment
171.
learning experience
172.
learning infrastructures
173.
Learning Lab
174.
learning management
175.
learning management system
176.
learning management systems
177.
learning methodology
178.
learning metrics
179.
learning models
180.
learning motivation
181.
learning objectives
182.
learning objects
183.
learning organization
184.
learning orientation
185.
learning outcomes
186.
learning process
187.
learning processes
188.
learning rate
189.
learning rate dependence on ownership form
190.
learning rate of organization
191.
learning region
192.
learning situation
193.
learning software agents
194.
learning styles
195.
learning systems
196.
learning technologies
197.
learning theories
198.
learning through the questionnaires
199.
learning university
200.
learning-to-rank
201.
lifelong learning
202.
mathematics students learning habits
203.
Meaningful learning
204.
measuring learning
205.
mobile learning
206.
model learning
207.
Multi-agent reinforcement learning
208.
mutual learning
209.
new learning models
210.
node embedding learning
211.
NREN e-learning
212.
on-device transfer learning
213.
online learning
214.
ontologies for learning systems
215.
ontology learning
216.
organisational learning
217.
organizational learning
218.
organizational learning measurement instruments
219.
organizational learning rate dependence on management
220.
organizational learning rate measurement
221.
outcome oriented learning
222.
peer‐to‐peer learning group
223.
personalised learning
224.
policy learning
225.
problem-based learning
226.
Problem-based learning (PBL)
227.
project learning
228.
project-based learning
229.
Q-learning
230.
Q-learning algorithm
231.
query learning
232.
regional learning
233.
reinforcement learning
234.
relative learning performance
235.
Remote learning
236.
research-oriented learning
237.
reusable learning objects
238.
scholarship of teaching and learning
239.
self learning software
240.
self learning system
241.
self-learning
242.
self-regulated learning
243.
semi-supervised learning
244.
smart learning
245.
smart learning environment
246.
social learning
247.
stochastic learning theory
248.
supervised learning
249.
supervised learning data
250.
task based learning
251.
team learning
252.
Technological learning
253.
the dimensions of the learning organisation
254.
the dimensions of the learning organization questionnaire (DLOQ)
255.
tools for interactive learning and teaching
256.
trans-disciplinary social-learning
257.
transfer learning
258.
true online reinforcement learning
259.
ubiquitous learning
260.
unsupervised learning
261.
urban learning center
262.
value of learning
263.
web and computerbased learning
264.
Web and computer-based learning
265.
virtual learning environment
266.
virtual learning factory
267.
work-based learning
268.
workplace learning
autor
1
1.
ELIXIR Machine Learning Focus Group
märksõna
1
1.
UNDP Urban Learning Center
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