Статті в журналах з теми "Small datasets"
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Agliari, Elena, Francesco Alemanno, Miriam Aquaro, Adriano Barra, Fabrizio Durante, and Ido Kanter. "Hebbian dreaming for small datasets." Neural Networks 173 (May 2024): 106174. http://dx.doi.org/10.1016/j.neunet.2024.106174.
Ingrassia, Salvatore, and Isabella Morlini. "Neural Network Modeling for Small Datasets." Technometrics 47, no. 3 (August 2005): 297–311. http://dx.doi.org/10.1198/004017005000000058.
Ricchiuto, Piero, Judy C. G. Sng, and Wilson Wen Bin Goh. "Analysing extremely small sized ratio datasets." International Journal of Bioinformatics Research and Applications 11, no. 3 (2015): 268. http://dx.doi.org/10.1504/ijbra.2015.069225.
Tuomo, Alasalmi, Jaakko Suutala, Juha Röning, and Heli Koskimäki. "Better Classifier Calibration for Small Datasets." ACM Transactions on Knowledge Discovery from Data 14, no. 3 (May 14, 2020): 1–19. http://dx.doi.org/10.1145/3385656.
Montalvão, J., R. Attux, and D. G. Silva. "Simple entropy estimator for small datasets." Electronics Letters 48, no. 17 (August 16, 2012): 1059–61. http://dx.doi.org/10.1049/el.2012.2002.
Khobragade, Vandana, M. S. Pradeep Kumar Patnaik, and Srinivasa Rao Sura. "Revaluating Pretraining in Small Size Training Sample Regime." International Journal of Electrical and Electronics Research 10, no. 3 (September 30, 2022): 694–704. http://dx.doi.org/10.37391/ijeer.100346.
Burmakova, Anastasiya, and Diana Kalibatienė. "Applying Fuzzy Inference and Machine Learning Methods for Prediction with a Small Dataset: A Case Study for Predicting the Consequences of Oil Spills on a Ground Environment." Applied Sciences 12, no. 16 (August 18, 2022): 8252. http://dx.doi.org/10.3390/app12168252.
Jamjoom, Mona. "The pertinent single-attribute-based classifier for small datasets classification." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (June 1, 2020): 3227. http://dx.doi.org/10.11591/ijece.v10i3.pp3227-3234.
Petráš, Jaroslav, Marek Pavlík, Ján Zbojovský, Ardian Hyseni, and Jozef Dudiak. "Benford’s Law in Electric Distribution Network." Mathematics 11, no. 18 (September 10, 2023): 3863. http://dx.doi.org/10.3390/math11183863.
Andonie, Răzvan. "Extreme Data Mining: Inference from Small Datasets." International Journal of Computers Communications & Control 5, no. 3 (September 1, 2010): 280. http://dx.doi.org/10.15837/ijccc.2010.3.2481.
Ku, C. J., and T. L. Fine. "A Bayesian Independence Test for Small Datasets." IEEE Transactions on Signal Processing 54, no. 10 (October 2006): 4026–31. http://dx.doi.org/10.1109/tsp.2006.880243.
Li, Der-Chiang, Hung-Yu Chen, and Qi-Shi Shi. "Learning from small datasets containing nominal attributes." Neurocomputing 291 (May 2018): 226–36. http://dx.doi.org/10.1016/j.neucom.2018.02.069.
Xu, Weihuang, Guohao Yu, Alina Zare, Brendan Zurweller, Diane L. Rowland, Joel Reyes-Cabrera, Felix B. Fritschi, Roser Matamala, and Thomas E. Juenger. "Overcoming small minirhizotron datasets using transfer learning." Computers and Electronics in Agriculture 175 (August 2020): 105466. http://dx.doi.org/10.1016/j.compag.2020.105466.
Xu, Zi’an, Yin Dai, Fayu Liu, Weibing Chen, Yue Liu, Lifu Shi, Sheng Liu, and Yuhang Zhou. "Swin MAE: Masked autoencoders for small datasets." Computers in Biology and Medicine 161 (July 2023): 107037. http://dx.doi.org/10.1016/j.compbiomed.2023.107037.
Bhalla, Vandna. "INNOVATIVE MODEL TO AUGMENT SMALL DATASETS FOR CLASSIFICATION." International Journal of Advanced Research 11, no. 04 (April 30, 2023): 313–19. http://dx.doi.org/10.21474/ijar01/16658.
Keum, Bitna, Juoh Sun, Woojin Lee, Seongheum Park, and Harksoo Kim. "Persona-Identified Chatbot through Small-Scale Modeling and Data Transformation." Electronics 13, no. 8 (April 9, 2024): 1409. http://dx.doi.org/10.3390/electronics13081409.
Bao, Yan, Frank Heilig, Chuo-Hsuan Lee, and Edward J. Lusk. "Full Range Testing of the Small Size Effect Bias for Benford Screening: A Note." International Journal of Economics and Finance 10, no. 6 (April 30, 2018): 47. http://dx.doi.org/10.5539/ijef.v10n6p47.
Sumalatha, M., and Latha Parthiban. "Augmentation of Predictive Competence of Non-Small Cell Lung Cancer Datasets through Feature Pre-Processing Techniques." EAI Endorsed Transactions on Pervasive Health and Technology 8, no. 5 (November 2, 2022): e1. http://dx.doi.org/10.4108/eetpht.v8i5.3169.
Bai, Long, Liangyu Wang, Tong Chen, Yuanhao Zhao, and Hongliang Ren. "Transformer-Based Disease Identification for Small-Scale Imbalanced Capsule Endoscopy Dataset." Electronics 11, no. 17 (August 31, 2022): 2747. http://dx.doi.org/10.3390/electronics11172747.
Bao, Yan, Chuo-Hsuan Lee, Frank Heilig, and Edward J. Lusk. "Empirical Information on the Small Size Effect Bias Relative to the False Positive Rejection Error for Benford Test-Screening." International Journal of Economics and Finance 10, no. 2 (January 3, 2018): 1. http://dx.doi.org/10.5539/ijef.v10n2p1.
Mabuni, D., and S. Aquter Babu. "High Accurate and a Variant of k-fold Cross Validation Technique for Predicting the Decision Tree Classifier Accuracy." International Journal of Innovative Technology and Exploring Engineering 10, no. 2 (January 10, 2021): 105–10. http://dx.doi.org/10.35940/ijitee.c8403.0110321.
Jaryani, Farhang, and Maryam Amiri. "A Pre-Trained Ensemble Model for Breast Cancer Grade Detection Based on Small Datasets." Iranian Journal of Health Sciences 11, no. 1 (January 1, 2023): 47–58. http://dx.doi.org/10.32598/ijhs.11.1.883.1.
Kim, Dongseob, Seungho Lee, Junsuk Choe, and Hyunjung Shim. "Weakly Supervised Semantic Segmentation for Driving Scenes." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (March 24, 2024): 2741–49. http://dx.doi.org/10.1609/aaai.v38i3.28053.
Xu, Xinkai, Hailan Zhang, Yan Ma, Kang Liu, Hong Bao, and Xu Qian. "TranSDet: Toward Effective Transfer Learning for Small-Object Detection." Remote Sensing 15, no. 14 (July 12, 2023): 3525. http://dx.doi.org/10.3390/rs15143525.
Davila Delgado, Juan Manuel, and Lukumon Oyedele. "Deep learning with small datasets: using autoencoders to address limited datasets in construction management." Applied Soft Computing 112 (November 2021): 107836. http://dx.doi.org/10.1016/j.asoc.2021.107836.
Marston, Louise, Janet L. Peacock, Keming Yu, Peter Brocklehurst, Sandra A. Calvert, Anne Greenough, and Neil Marlow. "Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets." Paediatric and Perinatal Epidemiology 23, no. 4 (July 2009): 380–92. http://dx.doi.org/10.1111/j.1365-3016.2009.01046.x.
Karunanithi, Sivarajan, Martin Simon, and Marcel H. Schulz. "Automated analysis of small RNA datasets with RAPID." PeerJ 7 (April 10, 2019): e6710. http://dx.doi.org/10.7717/peerj.6710.
Goyal, Gaurvi, Nicoletta Noceti, and Francesca Odone. "Cross-view action recognition with small-scale datasets." Image and Vision Computing 120 (April 2022): 104403. http://dx.doi.org/10.1016/j.imavis.2022.104403.
Singh, Gurpartap, Sunil Agrawal, and Balwinder Singh Sohi. "Handwritten Gurmukhi Digit Recognition System for Small Datasets." Traitement du Signal 37, no. 4 (October 10, 2020): 661–69. http://dx.doi.org/10.18280/ts.370416.
Mauldin, Taylor, Anne H. Ngu, Vangelis Metsis, and Marc E. Canby. "Ensemble Deep Learning on Wearables Using Small Datasets." ACM Transactions on Computing for Healthcare 2, no. 1 (December 30, 2020): 1–30. http://dx.doi.org/10.1145/3428666.
Li, Jingmei, Di Xue, Weifei Wu, and Jiaxiang Wang. "Incremental Learning for Malware Classification in Small Datasets." Security and Communication Networks 2020 (February 20, 2020): 1–12. http://dx.doi.org/10.1155/2020/6309243.
Baroni, Michel, Fabrice Barthélémy, and Mahdi Mokrane. "A repeat sales index robust to small datasets." Journal of Property Investment & Finance 29, no. 1 (February 8, 2011): 35–48. http://dx.doi.org/10.1108/14635781111100182.
von Ungern-Sternberg, Britta S., and Adrian Regli. "Big problem, small incidence, and large registry datasets." Lancet Respiratory Medicine 4, no. 1 (January 2016): 5–6. http://dx.doi.org/10.1016/s2213-2600(15)00519-6.
Vatian, A. S., A. A. Golubev, N. F. Gusarova, N. V. Dobrenko, A. A. Zubanenko, E. S. Kustova, A. A. Tatarinova, I. V. Tomilov, and G. F. Shovkoplyas. "Intelligent clinical decision support for small patient datasets." Scientific and Technical Journal of Information Technologies, Mechanics and Optics 23, no. 3 (June 1, 2023): 595–607. http://dx.doi.org/10.17586/2226-1494-2023-23-3-595-607.
Tanov, Vladislav. "Data-Centric Optimization Approach for Small, Imbalanced Datasets." Journal of information and organizational sciences 47, no. 1 (June 30, 2023): 167–77. http://dx.doi.org/10.31341/jios.47.1.9.
Wu, Yumei, Jingxiu Yao, Shuo Chang, and Bin Liu. "LIMCR: Less-Informative Majorities Cleaning Rule Based on Naïve Bayes for Imbalance Learning in Software Defect Prediction." Applied Sciences 10, no. 23 (November 24, 2020): 8324. http://dx.doi.org/10.3390/app10238324.
Perin, Vinicius, Samapriya Roy, Joe Kington, Thomas Harris, Mirela G. Tulbure, Noah Stone, Torben Barsballe, Michele Reba, and Mary A. Yaeger. "Monitoring Small Water Bodies Using High Spatial and Temporal Resolution Analysis Ready Datasets." Remote Sensing 13, no. 24 (December 20, 2021): 5176. http://dx.doi.org/10.3390/rs13245176.
Sheeny, Marcel, Andrew Wallace, and Sen Wang. "RADIO: Parameterized Generative Radar Data Augmentation for Small Datasets." Applied Sciences 10, no. 11 (June 2, 2020): 3861. http://dx.doi.org/10.3390/app10113861.
Li, Jindi, Kefeng Li, Guangyuan Zhang, Jiaqi Wang, Keming Li, and Yumin Yang. "Recognition of Dorsal Hand Vein in Small-Scale Sample Database Based on Fusion of ResNet and HOG Feature." Electronics 11, no. 17 (August 28, 2022): 2698. http://dx.doi.org/10.3390/electronics11172698.
Panda, Rameswar, Michele Merler, Mayoore S. Jaiswal, Hui Wu, Kandan Ramakrishnan, Ulrich Finkler, Chun-Fu Richard Chen, et al. "NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (May 18, 2021): 9294–302. http://dx.doi.org/10.1609/aaai.v35i10.17121.
Maack, Lennart, Lennart Holstein, and Alexander Schlaefer. "GANs for generation of synthetic ultrasound images from small datasets." Current Directions in Biomedical Engineering 8, no. 1 (July 1, 2022): 17–20. http://dx.doi.org/10.1515/cdbme-2022-0005.
Ahmed, Shouket Abdulrahman, Hazry Desa, and Abadal-Salam T. Hussain. "Aerial image semantic segmentation based on 3D fits a small dataset of 1D." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 4 (December 1, 2023): 2048. http://dx.doi.org/10.11591/ijai.v12.i4.pp2048-2054.
Ng, Wartini, Budiman Minasny, Brendan Malone, and Patrick Filippi. "In search of an optimum sampling algorithm for prediction of soil properties from infrared spectra." PeerJ 6 (October 3, 2018): e5722. http://dx.doi.org/10.7717/peerj.5722.
Zhang, Ruofan, Yi Wang, Ping Jiang, Jialiang Peng, and Hailin Chen. "IBSA_Net: A Network for Tomato Leaf Disease Identification Based on Transfer Learning with Small Samples." Applied Sciences 13, no. 7 (March 29, 2023): 4348. http://dx.doi.org/10.3390/app13074348.
Mu, Lingli, Lina Xian, Lihong Li, Gang Liu, Mi Chen, and Wei Zhang. "YOLO-Crater Model for Small Crater Detection." Remote Sensing 15, no. 20 (October 20, 2023): 5040. http://dx.doi.org/10.3390/rs15205040.
Shao, Ran, Xiao-Jun Bi, and Zheng Chen. "A novel hybrid transformer-CNN architecture for environmental microorganism classification." PLOS ONE 17, no. 11 (November 11, 2022): e0277557. http://dx.doi.org/10.1371/journal.pone.0277557.
Nguyen, Nhat-Duy, Tien Do, Thanh Duc Ngo, and Duy-Dinh Le. "An Evaluation of Deep Learning Methods for Small Object Detection." Journal of Electrical and Computer Engineering 2020 (April 27, 2020): 1–18. http://dx.doi.org/10.1155/2020/3189691.
Liu, Tengjun, Ying Chen, and Wanxuan Gu. "Copyright-Certified Distillation Dataset: Distilling One Million Coins into One Bitcoin with Your Private Key." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 5 (June 26, 2023): 6458–66. http://dx.doi.org/10.1609/aaai.v37i5.25794.
Finn, Michael P., Daniel R. Steinwand, Jason R. Trent, Robert A. Buehler, David M. Mattli, and Kristina Haruka Yamamoto. "A Program for Handling Map Projections of Small Scale Geospatial Raster Data." Cartographic Perspectives, no. 71 (September 24, 2012): 53–67. http://dx.doi.org/10.14714/cp71.61.
MacKinnon, James G. "Inference with Large Clustered Datasets." Articles 92, no. 4 (July 12, 2017): 649–65. http://dx.doi.org/10.7202/1040501ar.