Artículos de revistas sobre el tema "Artificial datasets"
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Serrano-Pérez, Jonathan y L. Enrique Sucar. "Artificial datasets for hierarchical classification". Expert Systems with Applications 182 (noviembre de 2021): 115218. http://dx.doi.org/10.1016/j.eswa.2021.115218.
Lychev, Andrey V. "Synthetic Data Generation for Data Envelopment Analysis". Data 8, n.º 10 (27 de septiembre de 2023): 146. http://dx.doi.org/10.3390/data8100146.
Petráš, Jaroslav, Marek Pavlík, Ján Zbojovský, Ardian Hyseni y Jozef Dudiak. "Benford’s Law in Electric Distribution Network". Mathematics 11, n.º 18 (10 de septiembre de 2023): 3863. http://dx.doi.org/10.3390/math11183863.
Dasari, Kishore Babu y Nagaraju Devarakonda. "TCP/UDP-Based Exploitation DDoS Attacks Detection Using AI Classification Algorithms with Common Uncorrelated Feature Subset Selected by Pearson, Spearman and Kendall Correlation Methods". Revue d'Intelligence Artificielle 36, n.º 1 (28 de febrero de 2022): 61–71. http://dx.doi.org/10.18280/ria.360107.
Kusetogullari, Huseyin, Amir Yavariabdi, Abbas Cheddad, Håkan Grahn y Johan Hall. "ARDIS: a Swedish historical handwritten digit dataset". Neural Computing and Applications 32, n.º 21 (29 de marzo de 2019): 16505–18. http://dx.doi.org/10.1007/s00521-019-04163-3.
Morgan, Maria, Carla Blank y Raed Seetan. "Plant disease prediction using classification algorithms". IAES International Journal of Artificial Intelligence (IJ-AI) 10, n.º 1 (1 de marzo de 2021): 257. http://dx.doi.org/10.11591/ijai.v10.i1.pp257-264.
Saul, Marcia y Shahin Rostami. "Assessing performance of artificial neural networks and re-sampling techniques for healthcare datasets". Health Informatics Journal 28, n.º 1 (enero de 2022): 146045822210871. http://dx.doi.org/10.1177/14604582221087109.
Gau, Michael-Lian, Huong-Yong Ting, Teck-Hock Toh, Pui-Ying Wong, Pei-Jun Woo, Su-Woan Wo y Gek-Ling Tan. "Effectiveness of Using Artificial Intelligence for Early Child Development Screening". Green Intelligent Systems and Applications 3, n.º 1 (9 de mayo de 2023): 1–13. http://dx.doi.org/10.53623/gisa.v3i1.229.
GHAFFARI, REZA, IOAN GROSU, DACIANA ILIESCU, EVOR HINES y MARK LEESON. "DIMENSIONALITY REDUCTION FOR SENSORY DATASETS BASED ON MASTER–SLAVE SYNCHRONIZATION OF LORENZ SYSTEM". International Journal of Bifurcation and Chaos 23, n.º 05 (mayo de 2013): 1330013. http://dx.doi.org/10.1142/s0218127413300139.
Pavlov, Nikolay A., Anna E. Andreychenko, Anton V. Vladzymyrskyy, Anush A. Revazyan, Yury S. Kirpichev y Sergey P. Morozov. "Reference medical datasets (MosMedData) for independent external evaluation of algorithms based on artificial intelligence in diagnostics". Digital Diagnostics 2, n.º 1 (30 de abril de 2021): 49–66. http://dx.doi.org/10.17816/dd60635.
Akgül, İsmail, Volkan Kaya y Özge Zencir Tanır. "A novel hybrid system for automatic detection of fish quality from eye and gill color characteristics using transfer learning technique". PLOS ONE 18, n.º 4 (25 de abril de 2023): e0284804. http://dx.doi.org/10.1371/journal.pone.0284804.
Vasilev, Y. A., T. M. Bobrovskaya, K. M. Arzamasov, S. F. Chetverikov, A. V. Vladzymyrskyy, O. V. Omelyanskaya, A. E. Andreychenko, N. A. Pavlov y L. N. Anishchenko. "Medical datasets for machine learning: fundamental principles of standartization and systematization". Manager Zdravookhranenia, n.º 4 (7 de junio de 2023): 28–41. http://dx.doi.org/10.21045/1811-0185-2023-4-28-41.
Xie, Ning-Ning, Fang-Fang Wang, Jue Zhou, Chang Liu y Fan Qu. "Establishment and Analysis of a Combined Diagnostic Model of Polycystic Ovary Syndrome with Random Forest and Artificial Neural Network". BioMed Research International 2020 (20 de agosto de 2020): 1–13. http://dx.doi.org/10.1155/2020/2613091.
Antczak, Karol. "On regularization properties of artificial datasets for deep learning". Computer Science and Mathematical Modelling, n.º 9/2019 (30 de noviembre de 2019): 13–18. http://dx.doi.org/10.5604/01.3001.0013.6599.
Mathur, Varoon, Caitlin Lustig y Elizabeth Kaziunas. "Disordering Datasets". Proceedings of the ACM on Human-Computer Interaction 6, CSCW2 (7 de noviembre de 2022): 1–33. http://dx.doi.org/10.1145/3555141.
Alshayeb, Mohammad y Mashaan A. Alshammari. "The Effect of the Dataset Size on the Accuracy of Software Defect Prediction Models: An Empirical Study". Inteligencia Artificial 24, n.º 68 (26 de octubre de 2021): 72–88. http://dx.doi.org/10.4114/intartif.vol24iss68pp72-88.
Orelaja, Adeyinka, Chidubem Ejiofor, Samuel Sarpong, Success Imakuh, Christian Bassey, Iheanyichukwu Opara, Josiah Nii Armah Tettey y Omolola Akinola. "Attribute-specific Cyberbullying Detection Using Artificial Intelligence". Journal of Electronic & Information Systems 6, n.º 1 (28 de febrero de 2024): 10–21. http://dx.doi.org/10.30564/jeis.v6i1.6206.
Wilde, Henry, Vincent Knight y Jonathan Gillard. "Evolutionary dataset optimisation: learning algorithm quality through evolution". Applied Intelligence 50, n.º 4 (27 de diciembre de 2019): 1172–91. http://dx.doi.org/10.1007/s10489-019-01592-4.
Harper, F. Maxwell y Joseph A. Konstan. "The MovieLens Datasets". ACM Transactions on Interactive Intelligent Systems 5, n.º 4 (7 de enero de 2016): 1–19. http://dx.doi.org/10.1145/2827872.
Sgantzos, Konstantinos y Ian Grigg. "Artificial Intelligence Implementations on the Blockchain. Use Cases and Future Applications". Future Internet 11, n.º 8 (2 de agosto de 2019): 170. http://dx.doi.org/10.3390/fi11080170.
Ansari, Shaheer, Afida Ayob, Molla Shahadat Hossain Lipu, Aini Hussain y Mohamad Hanif Md Saad. "Multi-Channel Profile Based Artificial Neural Network Approach for Remaining Useful Life Prediction of Electric Vehicle Lithium-Ion Batteries". Energies 14, n.º 22 (11 de noviembre de 2021): 7521. http://dx.doi.org/10.3390/en14227521.
Knoblock, Craig A. y Pedro Szekely. "Exploiting Semantics for Big Data Integration". AI Magazine 36, n.º 1 (25 de marzo de 2015): 25–38. http://dx.doi.org/10.1609/aimag.v36i1.2565.
Chiang, Cheng-Han y Hung-yi Lee. "On the Transferability of Pre-trained Language Models: A Study from Artificial Datasets". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 10 (28 de junio de 2022): 10518–25. http://dx.doi.org/10.1609/aaai.v36i10.21295.
Chen, M., V. Rotemberg, J. Lester, R. Novoa, A. Chiou y R. Daneshjou. "662 Evaluation of diagnosis diversity in artificial intelligence datasets". Journal of Investigative Dermatology 142, n.º 8 (agosto de 2022): S114. http://dx.doi.org/10.1016/j.jid.2022.05.673.
Wahid, Kareem A., Enrico Glerean, Jaakko Sahlsten, Joel Jaskari, Kimmo Kaski, Mohamed A. Naser, Renjie He, Abdallah S. R. Mohamed y Clifton D. Fuller. "Artificial Intelligence for Radiation Oncology Applications Using Public Datasets". Seminars in Radiation Oncology 32, n.º 4 (octubre de 2022): 400–414. http://dx.doi.org/10.1016/j.semradonc.2022.06.009.
Mesquita, Diego P. P., João Paulo P. Gomes y Leonardo R. Rodrigues. "Artificial Neural Networks with Random Weights for Incomplete Datasets". Neural Processing Letters 50, n.º 3 (6 de marzo de 2019): 2345–72. http://dx.doi.org/10.1007/s11063-019-10012-0.
Altman, RB. "Artificial intelligence (AI) systems for interpreting complex medical datasets". Clinical Pharmacology & Therapeutics 101, n.º 5 (17 de marzo de 2017): 585–86. http://dx.doi.org/10.1002/cpt.650.
Uma, Alexandra N., Tommaso Fornaciari, Dirk Hovy, Silviu Paun, Barbara Plank y Massimo Poesio. "Learning from Disagreement: A Survey". Journal of Artificial Intelligence Research 72 (27 de diciembre de 2021): 1385–470. http://dx.doi.org/10.1613/jair.1.12752.
Mehta, Harshkumar y Kalpdrum Passi. "Social Media Hate Speech Detection Using Explainable Artificial Intelligence (XAI)". Algorithms 15, n.º 8 (17 de agosto de 2022): 291. http://dx.doi.org/10.3390/a15080291.
Aggarwal, Mukul, Amod Kumar Tiwari y M. Partha Sarathi. "Comparative Analysis of Deep Learning Models on Brain Tumor Segmentation Datasets: BraTS 2015-2020 Datasets". Revue d'Intelligence Artificielle 36, n.º 6 (31 de diciembre de 2022): 863–71. http://dx.doi.org/10.18280/ria.360606.
Dewangan, Neha, Kavita Thakur, Sunandan Mandal y Bikesh Kumar Singh. "Time-Frequency Image-based Speech Emotion Recognition using Artificial Neural Network". Journal of Ravishankar University (PART-B) 36, n.º 2 (31 de diciembre de 2023): 144–57. http://dx.doi.org/10.52228/jrub.2023-36-2-10.
Dognin, Pierre, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff, Richard A. Young y Brian Belgodere. "Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge". Journal of Artificial Intelligence Research 73 (31 de enero de 2022): 437–59. http://dx.doi.org/10.1613/jair.1.13113.
Polymenis, Ioannis, Maryam Haroutunian, Rose Norman y David Trodden. "Virtual Underwater Datasets for Autonomous Inspections". Journal of Marine Science and Engineering 10, n.º 9 (13 de septiembre de 2022): 1289. http://dx.doi.org/10.3390/jmse10091289.
Landes, Juergen y Jon Williamson. "Objective Bayesian Nets for Integrating Consistent Datasets". Journal of Artificial Intelligence Research 74 (27 de mayo de 2022): 393–458. http://dx.doi.org/10.1613/jair.1.13363.
Rodriguez-Baena, Domingo S. "Extracting and validating biclusters from binary datasets". AI Communications 26, n.º 4 (2013): 417–18. http://dx.doi.org/10.3233/aic-130570.
Alfonso Perez, Gerardo y Javier Caballero Villarraso. "Alzheimer Identification through DNA Methylation and Artificial Intelligence Techniques". Mathematics 9, n.º 19 (4 de octubre de 2021): 2482. http://dx.doi.org/10.3390/math9192482.
Vobecký, Antonín, David Hurych, Michal Uřičář, Patrick Pérez y Josef Sivic. "Artificial Dummies for Urban Dataset Augmentation". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 3 (18 de mayo de 2021): 2692–700. http://dx.doi.org/10.1609/aaai.v35i3.16373.
Merdas, Hussam y Ayad Mousa. "Forecasting Sales of Iraqi Dates Using Artificial Intelligence". Iraqi Journal of Intelligent Computing and Informatics (IJICI) 2, n.º 2 (17 de noviembre de 2023): 130–45. http://dx.doi.org/10.52940/ijici.v2i2.47.
Kang, Myounghee, Takeshi Nakamura y Akira Hamano. "A methodology for acoustic and geospatial analysis of diverse artificial-reef datasets". ICES Journal of Marine Science 68, n.º 10 (2 de septiembre de 2011): 2210–21. http://dx.doi.org/10.1093/icesjms/fsr141.
Agliari, Elena, Francesco Alemanno, Miriam Aquaro, Adriano Barra, Fabrizio Durante y Ido Kanter. "Hebbian dreaming for small datasets". Neural Networks 173 (mayo de 2024): 106174. http://dx.doi.org/10.1016/j.neunet.2024.106174.
Chiaia, Bernardino y Valerio De Biagi. "Archetypal Use of Artificial Intelligence for Bridge Structural Monitoring". Applied Sciences 10, n.º 20 (14 de octubre de 2020): 7157. http://dx.doi.org/10.3390/app10207157.
Kamp, R. G. y H. H. G. Savenije. "Optimising training data for ANNs with Genetic Algorithms". Hydrology and Earth System Sciences 10, n.º 4 (7 de septiembre de 2006): 603–8. http://dx.doi.org/10.5194/hess-10-603-2006.
Perafan-Lopez, Juan Carlos, Valeria Lucía Ferrer-Gregory, César Nieto-Londoño y Julián Sierra-Pérez. "Performance Analysis and Architecture of a Clustering Hybrid Algorithm Called FA+GA-DBSCAN Using Artificial Datasets". Entropy 24, n.º 7 (25 de junio de 2022): 875. http://dx.doi.org/10.3390/e24070875.
Adolfo, Cid Mathew Santiago, Hassan Chizari, Thu Yein Win y Salah Al-Majeed. "Sample Reduction for Physiological Data Analysis Using Principal Component Analysis in Artificial Neural Network". Applied Sciences 11, n.º 17 (6 de septiembre de 2021): 8240. http://dx.doi.org/10.3390/app11178240.
Guha, Ritam, Manosij Ghosh, Pawan Kumar Singh, Ram Sarkar y Mita Nasipuri. "M-HMOGA: A New Multi-Objective Feature Selection Algorithm for Handwritten Numeral Classification". Journal of Intelligent Systems 29, n.º 1 (14 de junio de 2019): 1453–67. http://dx.doi.org/10.1515/jisys-2019-0064.
Aliyari, Mostafa y Yonas Zewdu Ayele. "Application of Artificial Neural Networks for Power Load Prediction in Critical Infrastructure: A Comparative Case Study". Applied System Innovation 6, n.º 6 (30 de noviembre de 2023): 115. http://dx.doi.org/10.3390/asi6060115.
Khan, Somaiya y Ali Khan. "SkinViT: A transformer based method for Melanoma and Nonmelanoma classification". PLOS ONE 18, n.º 12 (27 de diciembre de 2023): e0295151. http://dx.doi.org/10.1371/journal.pone.0295151.
Park, Min-Ho, Chang-Min Lee, Antony John Nyongesa, Hee-Joo Jang, Jae-Hyuk Choi, Jae-Jung Hur y Won-Ju Lee. "Prediction of Emission Characteristics of Generator Engine with Selective Catalytic Reduction Using Artificial Intelligence". Journal of Marine Science and Engineering 10, n.º 8 (13 de agosto de 2022): 1118. http://dx.doi.org/10.3390/jmse10081118.
Nwokoma, Faith, Justin Foreman y Cajetan M. Akujuobi. "Effective Data Reduction Using Discriminative Feature Selection Based on Principal Component Analysis". Machine Learning and Knowledge Extraction 6, n.º 2 (3 de abril de 2024): 789–99. http://dx.doi.org/10.3390/make6020037.
Douzas, Georgios, Maria Lechleitner y Fernando Bacao. "Improving the quality of predictive models in small data GSDOT: A new algorithm for generating synthetic data". PLOS ONE 17, n.º 4 (7 de abril de 2022): e0265626. http://dx.doi.org/10.1371/journal.pone.0265626.