Artículos de revistas sobre el tema "Black-Box Classifier"
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Lee, Hansoo y Sungshin Kim. "Black-Box Classifier Interpretation Using Decision Tree and Fuzzy Logic-Based Classifier Implementation". International Journal of Fuzzy Logic and Intelligent Systems 16, n.º 1 (31 de marzo de 2016): 27–35. http://dx.doi.org/10.5391/ijfis.2016.16.1.27.
Texto completoRajabi, Arezoo, Mahdieh Abbasi, Rakesh B. Bobba y Kimia Tajik. "Adversarial Images Against Super-Resolution Convolutional Neural Networks for Free". Proceedings on Privacy Enhancing Technologies 2022, n.º 3 (julio de 2022): 120–39. http://dx.doi.org/10.56553/popets-2022-0065.
Texto completoJi, Disi, Robert L. Logan, Padhraic Smyth y Mark Steyvers. "Active Bayesian Assessment of Black-Box Classifiers". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 9 (18 de mayo de 2021): 7935–44. http://dx.doi.org/10.1609/aaai.v35i9.16968.
Texto completoTran, Thien Q., Kazuto Fukuchi, Youhei Akimoto y Jun Sakuma. "Unsupervised Causal Binary Concepts Discovery with VAE for Black-Box Model Explanation". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 9 (28 de junio de 2022): 9614–22. http://dx.doi.org/10.1609/aaai.v36i9.21195.
Texto completoPark, Hosung, Gwonsang Ryu y Daeseon Choi. "Partial Retraining Substitute Model for Query-Limited Black-Box Attacks". Applied Sciences 10, n.º 20 (14 de octubre de 2020): 7168. http://dx.doi.org/10.3390/app10207168.
Texto completoLou, Chenlu y Xiang Pan. "Detect Black Box Signals with Enhanced Spectrum and Support Vector Classifier". Journal of Physics: Conference Series 1438 (enero de 2020): 012003. http://dx.doi.org/10.1088/1742-6596/1438/1/012003.
Texto completoChen, Pengpeng, Hailong Sun, Yongqiang Yang y Zhijun Chen. "Adversarial Learning from Crowds". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 5 (28 de junio de 2022): 5304–12. http://dx.doi.org/10.1609/aaai.v36i5.20467.
Texto completoMahmood, Kaleel, Deniz Gurevin, Marten van Dijk y Phuoung Ha Nguyen. "Beware the Black-Box: On the Robustness of Recent Defenses to Adversarial Examples". Entropy 23, n.º 10 (18 de octubre de 2021): 1359. http://dx.doi.org/10.3390/e23101359.
Texto completoHartono, Pitoyo. "A transparent cancer classifier". Health Informatics Journal 26, n.º 1 (31 de diciembre de 2018): 190–204. http://dx.doi.org/10.1177/1460458218817800.
Texto completoMasuda, Haruki, Tsunato Nakai, Kota Yoshida, Takaya Kubota, Mitsuru Shiozaki y Takeshi Fujino. "Black-Box Adversarial Attack against Deep Neural Network Classifier Utilizing Quantized Probability Output". Journal of Signal Processing 24, n.º 4 (15 de julio de 2020): 145–48. http://dx.doi.org/10.2299/jsp.24.145.
Texto completoPark, Dongjin y Kyungkoo Jun. "Vehicle Plate Detection in Car Black Box Video". Advances in Multimedia 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/7587841.
Texto completoKim, Jae Myung, Hyungjin Kim, Chanwoo Park y Jungwoo Lee. "REST: Performance Improvement of a Black Box Model via RL-Based Spatial Transformation". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 07 (3 de abril de 2020): 11262–69. http://dx.doi.org/10.1609/aaai.v34i07.6786.
Texto completoLin, Zhen, Lucas Glass, M. Brandon Westover, Cao Xiao y Jimeng Sun. "SCRIB: Set-Classifier with Class-Specific Risk Bounds for Blackbox Models". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 7 (28 de junio de 2022): 7497–505. http://dx.doi.org/10.1609/aaai.v36i7.20714.
Texto completoNauta, Meike, Ricky Walsh, Adam Dubowski y Christin Seifert. "Uncovering and Correcting Shortcut Learning in Machine Learning Models for Skin Cancer Diagnosis". Diagnostics 12, n.º 1 (24 de diciembre de 2021): 40. http://dx.doi.org/10.3390/diagnostics12010040.
Texto completoMayr, Franz, Sergio Yovine y Ramiro Visca. "Property Checking with Interpretable Error Characterization for Recurrent Neural Networks". Machine Learning and Knowledge Extraction 3, n.º 1 (12 de febrero de 2021): 205–27. http://dx.doi.org/10.3390/make3010010.
Texto completoLapid, Raz, Zvika Haramaty y Moshe Sipper. "An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Convolutional Neural Networks". Algorithms 15, n.º 11 (31 de octubre de 2022): 407. http://dx.doi.org/10.3390/a15110407.
Texto completoCombs, Kara, Mary Fendley y Trevor Bihl. "A Preliminary Look at Heuristic Analysis for Assessing Artificial Intelligence Explainability". WSEAS TRANSACTIONS ON COMPUTER RESEARCH 8 (1 de junio de 2020): 61–72. http://dx.doi.org/10.37394/232018.2020.8.9.
Texto completoAlahmed, Shahad, Qutaiba Alasad, Maytham M. Hammood, Jiann-Shiun Yuan y Mohammed Alawad. "Mitigation of Black-Box Attacks on Intrusion Detection Systems-Based ML". Computers 11, n.º 7 (20 de julio de 2022): 115. http://dx.doi.org/10.3390/computers11070115.
Texto completoRostami, Mehrdad y Mourad Oussalah. "Cancer prediction using graph-based gene selection and explainable classifier". Finnish Journal of eHealth and eWelfare 14, n.º 1 (14 de abril de 2022): 61–78. http://dx.doi.org/10.23996/fjhw.111772.
Texto completoDu, Xiaohu, Jie Yu, Zibo Yi, Shasha Li, Jun Ma, Yusong Tan y Qinbo Wu. "A Hybrid Adversarial Attack for Different Application Scenarios". Applied Sciences 10, n.º 10 (21 de mayo de 2020): 3559. http://dx.doi.org/10.3390/app10103559.
Texto completoBruni, Renato, Gianpiero Bianchi y Pasquale Papa. "Hyperparameter Black-Box Optimization to Improve the Automatic Classification of Support Tickets". Algorithms 16, n.º 1 (10 de enero de 2023): 46. http://dx.doi.org/10.3390/a16010046.
Texto completoFong, Simon. "Using Hierarchical Time Series Clustering Algorithm and Wavelet Classifier for Biometric Voice Classification". Journal of Biomedicine and Biotechnology 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/215019.
Texto completoWang, Huaijun, Ruomeng Ke, Junhuai Li, Yang An, Kan Wang y Lei Yu. "A correlation-based binary particle swarm optimization method for feature selection in human activity recognition". International Journal of Distributed Sensor Networks 14, n.º 4 (abril de 2018): 155014771877278. http://dx.doi.org/10.1177/1550147718772785.
Texto completoAlharbi, Basma, Zhenwen Liang, Jana M. Aljindan, Ammar K. Agnia y Xiangliang Zhang. "Explainable and Interpretable Anomaly Detection Models for Production Data". SPE Journal 27, n.º 01 (30 de noviembre de 2021): 349–63. http://dx.doi.org/10.2118/208586-pa.
Texto completoZarnelly, Zarnelly. "KLASIFIKASI PERMASALAHAN AGENSTOK MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER PADA PT. HPAI-PEKANBARU". Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi 5, n.º 2 (15 de agosto de 2019): 208. http://dx.doi.org/10.24014/rmsi.v5i2.7611.
Texto completoSudars, Kaspars, Ivars Namatēvs y Kaspars Ozols. "Improving Performance of the PRYSTINE Traffic Sign Classification by Using a Perturbation-Based Explainability Approach". Journal of Imaging 8, n.º 2 (30 de enero de 2022): 30. http://dx.doi.org/10.3390/jimaging8020030.
Texto completoY. A. Amer, Ahmed, Julie Vranken, Femke Wouters, Dieter Mesotten, Pieter Vandervoort, Valerie Storms, Stijn Luca, Bart Vanrumste y Jean-Marie Aerts. "Feature Engineering for ICU Mortality Prediction Based on Hourly to Bi-Hourly Measurements". Applied Sciences 9, n.º 17 (27 de agosto de 2019): 3525. http://dx.doi.org/10.3390/app9173525.
Texto completoWei, Chih-Chiang, Gene Jiing-Yun You, Li Chen, Chien-Chang Chou y Jinsheng Roan. "Diagnosing Rain Occurrences Using Passive Microwave Imagery: A Comparative Study on Probabilistic Graphical Models and “Black Box” Models". Journal of Atmospheric and Oceanic Technology 32, n.º 10 (octubre de 2015): 1729–44. http://dx.doi.org/10.1175/jtech-d-14-00164.1.
Texto completoAlfarra, Motasem, Juan C. Perez, Ali Thabet, Adel Bibi, Philip H. S. Torr y Bernard Ghanem. "Combating Adversaries with Anti-adversaries". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 6 (28 de junio de 2022): 5992–6000. http://dx.doi.org/10.1609/aaai.v36i6.20545.
Texto completoAslam, Nida, Irfan Ullah Khan, Samiha Mirza, Alanoud AlOwayed, Fatima M. Anis, Reef M. Aljuaid y Reham Baageel. "Interpretable Machine Learning Models for Malicious Domains Detection Using Explainable Artificial Intelligence (XAI)". Sustainability 14, n.º 12 (16 de junio de 2022): 7375. http://dx.doi.org/10.3390/su14127375.
Texto completoJaafreh, Russlan, Jung-Gu Kim y Kotiba Hamad. "Interpretable Machine Learning Analysis of Stress Concentration in Magnesium: An Insight beyond the Black Box of Predictive Modeling". Crystals 12, n.º 9 (2 de septiembre de 2022): 1247. http://dx.doi.org/10.3390/cryst12091247.
Texto completoZhou, Yuxuan, Huangxun Chen, Chenyu Huang y Qian Zhang. "WiAdv". Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, n.º 2 (4 de julio de 2022): 1–25. http://dx.doi.org/10.1145/3534618.
Texto completoXu, Zhiwu, Cheng Wen, Shengchao Qin y Mengda He. "Extracting automata from neural networks using active learning". PeerJ Computer Science 7 (19 de abril de 2021): e436. http://dx.doi.org/10.7717/peerj-cs.436.
Texto completoSuri, Anshuman y David Evans. "Formalizing and Estimating Distribution Inference Risks". Proceedings on Privacy Enhancing Technologies 2022, n.º 4 (octubre de 2022): 528–51. http://dx.doi.org/10.56553/popets-2022-0121.
Texto completoDe Falco, Ivanoe, Giuseppe De Pietro y Giovanna Sannino. "A Two-Step Approach for Classification in Alzheimer’s Disease". Sensors 22, n.º 11 (24 de mayo de 2022): 3966. http://dx.doi.org/10.3390/s22113966.
Texto completoPatil, Shruti, Vijayakumar Varadarajan, Siddiqui Mohd Mazhar, Abdulwodood Sahibzada, Nihal Ahmed, Onkar Sinha, Satish Kumar, Kailash Shaw y Ketan Kotecha. "Explainable Artificial Intelligence for Intrusion Detection System". Electronics 11, n.º 19 (27 de septiembre de 2022): 3079. http://dx.doi.org/10.3390/electronics11193079.
Texto completoCorley, Becky, Sofia Koukoura, James Carroll y Alasdair McDonald. "Combination of Thermal Modelling and Machine Learning Approaches for Fault Detection in Wind Turbine Gearboxes". Energies 14, n.º 5 (3 de marzo de 2021): 1375. http://dx.doi.org/10.3390/en14051375.
Texto completoChen, Kuan-Yung, Hsi-Chieh Lee, Tsung-Chieh Lin, Chih-Ying Lee y Zih-Ping Ho. "Deep Learning Algorithms with LIME and Similarity Distance Analysis on COVID-19 Chest X-ray Dataset". International Journal of Environmental Research and Public Health 20, n.º 5 (28 de febrero de 2023): 4330. http://dx.doi.org/10.3390/ijerph20054330.
Texto completoCofre-Martel, Sergio, Enrique Lopez Droguett y Mohammad Modarres. "Remaining Useful Life Estimation through Deep Learning Partial Differential Equation Models: A Framework for Degradation Dynamics Interpretation Using Latent Variables". Shock and Vibration 2021 (27 de mayo de 2021): 1–15. http://dx.doi.org/10.1155/2021/9937846.
Texto completoJung, Jiyoon, Eunsu Kim, Hyeseong Lee, Sung Hak Lee y Sangjeong Ahn. "Automated Hybrid Model for Detecting Perineural Invasion in the Histology of Colorectal Cancer". Applied Sciences 12, n.º 18 (13 de septiembre de 2022): 9159. http://dx.doi.org/10.3390/app12189159.
Texto completoCandelieri, Antonio y Francesco Archetti. "Sparsifying to optimize over multiple information sources: an augmented Gaussian process based algorithm". Structural and Multidisciplinary Optimization 64, n.º 1 (5 de abril de 2021): 239–55. http://dx.doi.org/10.1007/s00158-021-02882-7.
Texto completoHildebrandt, Marcel, Jorge Andres Quintero Serna, Yunpu Ma, Martin Ringsquandl, Mitchell Joblin y Volker Tresp. "Reasoning on Knowledge Graphs with Debate Dynamics". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 4123–31. http://dx.doi.org/10.1609/aaai.v34i04.6600.
Texto completoShao, Xiaoting, Arseny Skryagin, Wolfgang Stammer, Patrick Schramowski y Kristian Kersting. "Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 11 (18 de mayo de 2021): 9533–40. http://dx.doi.org/10.1609/aaai.v35i11.17148.
Texto completoMoskalenko, V. V., A. S. Moskalenko, A. G. Korobov y M. O. Zaretsky. "IMAGE CLASSIFIER RESILIENT TO ADVERSARIAL ATTACKS, FAULT INJECTIONS AND CONCEPT DRIFT – MODEL ARCHITECTURE AND TRAINING ALGORITHM". Radio Electronics, Computer Science, Control, n.º 3 (16 de octubre de 2022): 86. http://dx.doi.org/10.15588/1607-3274-2022-3-9.
Texto completoGozzi, Noemi, Edoardo Giacomello, Martina Sollini, Margarita Kirienko, Angela Ammirabile, Pierluca Lanzi, Daniele Loiacono y Arturo Chiti. "Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs". Diagnostics 12, n.º 9 (28 de agosto de 2022): 2084. http://dx.doi.org/10.3390/diagnostics12092084.
Texto completoSteiner, Margaret C., Keylie M. Gibson y Keith A. Crandall. "Drug Resistance Prediction Using Deep Learning Techniques on HIV-1 Sequence Data". Viruses 12, n.º 5 (19 de mayo de 2020): 560. http://dx.doi.org/10.3390/v12050560.
Texto completoMahmood, Asad, Faizan Ahmad, Zubair Shafiq, Padmini Srinivasan y Fareed Zaffar. "A Girl Has No Name: Automated Authorship Obfuscation using Mutant-X". Proceedings on Privacy Enhancing Technologies 2019, n.º 4 (1 de octubre de 2019): 54–71. http://dx.doi.org/10.2478/popets-2019-0058.
Texto completoYamashkin, Anatoliy y Stanislav Yamashkin. "Analysis of the Inerka polygon metageosystems by means of Ensembles of machine learning models". InterCarto. InterGIS 28, n.º 1 (2022): 613–28. http://dx.doi.org/10.35595/2414-9179-2022-1-28-613-628.
Texto completoSiino, Marco, Elisa Di Nuovo, Ilenia Tinnirello y Marco La Cascia. "Fake News Spreaders Detection: Sometimes Attention Is Not All You Need". Information 13, n.º 9 (9 de septiembre de 2022): 426. http://dx.doi.org/10.3390/info13090426.
Texto completoZafar, Muhammad Rehman y Naimul Khan. "Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability". Machine Learning and Knowledge Extraction 3, n.º 3 (30 de junio de 2021): 525–41. http://dx.doi.org/10.3390/make3030027.
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