Статті в журналах з теми "Multi-modal Machine Learning"
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Liang, Haotian, and Zhanqing Wang. "Hierarchical Attention Networks for Multimodal Machine Learning." Journal of Physics: Conference Series 2218, no. 1 (March 1, 2022): 012020. http://dx.doi.org/10.1088/1742-6596/2218/1/012020.
Повний текст джерелаNachiappan, Balusamy, N. Rajkumar, C. Viji, and Mohanraj A. "Artificial and Deceitful Faces Detection Using Machine Learning." Salud, Ciencia y Tecnología - Serie de Conferencias 3 (March 11, 2024): 611. http://dx.doi.org/10.56294/sctconf2024611.
Повний текст джерелаLiu, Ang, Tianying Lin, Hailong Han, Xiaopei Zhang, Ze Chen, Fuwan Gan, Haibin Lv, and Xiaoping Liu. "Analyzing modal power in multi-mode waveguide via machine learning." Optics Express 26, no. 17 (August 10, 2018): 22100. http://dx.doi.org/10.1364/oe.26.022100.
Повний текст джерелаLiu, Huaping, Jing Fang, Xinying Xu, and Fuchun Sun. "Surface Material Recognition Using Active Multi-modal Extreme Learning Machine." Cognitive Computation 10, no. 6 (July 4, 2018): 937–50. http://dx.doi.org/10.1007/s12559-018-9571-z.
Повний текст джерелаWei, Jie, Huaping Liu, Gaowei Yan, and Fuchun Sun. "Robotic grasping recognition using multi-modal deep extreme learning machine." Multidimensional Systems and Signal Processing 28, no. 3 (March 3, 2016): 817–33. http://dx.doi.org/10.1007/s11045-016-0389-0.
Повний текст джерелаA, Mr Balaji. "Extracting Audio from Image Using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (April 24, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem31532.
Повний текст джерелаAsim, Yousra, Basit Raza, Ahmad Kamran Malik, Saima Rathore, Lal Hussain, and Mohammad Aksam Iftikhar. "A multi-modal, multi-atlas-based approach for Alzheimer detection via machine learning." International Journal of Imaging Systems and Technology 28, no. 2 (January 10, 2018): 113–23. http://dx.doi.org/10.1002/ima.22263.
Повний текст джерелаG, Nandhini, and Santosh K. Balivada. "Multi-Modal Feature Integration in Machine Learning Predictions for Cardiovascular Diseases." International Journal of Health Technology and Innovation 2, no. 03 (December 7, 2023): 15–18. http://dx.doi.org/10.60142/ijhti.v2i03.03.
Повний текст джерелаLiu, Huaping, Fengxue Li, Xinying Xu, and Fuchun Sun. "Multi-modal local receptive field extreme learning machine for object recognition." Neurocomputing 277 (February 2018): 4–11. http://dx.doi.org/10.1016/j.neucom.2017.04.077.
Повний текст джерелаLamichhane, Bidhan, Dinal Jayasekera, Rachel Jakes, Matthew F. Glasser, Justin Zhang, Chunhui Yang, Derayvia Grimes, et al. "Multi-modal biomarkers of low back pain: A machine learning approach." NeuroImage: Clinical 29 (2021): 102530. http://dx.doi.org/10.1016/j.nicl.2020.102530.
Повний текст джерелаHuang, Haiming, Junhao Lin, Linyuan Wu, Bin Fang, Zhenkun Wen, and Fuchun Sun. "Machine learning-based multi-modal information perception for soft robotic hands." Tsinghua Science and Technology 25, no. 2 (April 2020): 255–69. http://dx.doi.org/10.26599/tst.2019.9010009.
Повний текст джерелаHe, Liqi, Zuchao Li, Xiantao Cai, and Ping Wang. "Multi-Modal Latent Space Learning for Chain-of-Thought Reasoning in Language Models." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 16 (March 24, 2024): 18180–87. http://dx.doi.org/10.1609/aaai.v38i16.29776.
Повний текст джерелаZhang, Lingyu, Xu Geng, Zhiwei Qin, Hongjun Wang, Xiao Wang, Ying Zhang, Jian Liang, Guobin Wu, Xuan Song, and Yunhai Wang. "Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting." Sustainability 14, no. 19 (September 29, 2022): 12397. http://dx.doi.org/10.3390/su141912397.
Повний текст джерелаEhiabhi, Jolly, and Haifeng Wang. "A Systematic Review of Machine Learning Models in Mental Health Analysis Based on Multi-Channel Multi-Modal Biometric Signals." BioMedInformatics 3, no. 1 (March 1, 2023): 193–219. http://dx.doi.org/10.3390/biomedinformatics3010014.
Повний текст джерелаBhatt, Saachin, Mustansar Ghazanfar, and Mohammad Hossein Amirhosseini. "Sentiment-Driven Cryptocurrency Price Prediction: A Machine Learning Approach Utilizing Historical Data and Social Media Sentiment Analysis." Machine Learning and Applications: An International Journal 10, no. 2/3 (September 28, 2023): 01–15. http://dx.doi.org/10.5121/mlaij.2023.10301.
Повний текст джерелаIslam, Kazi Aminul, Mohammad Shahab Uddin, Chiman Kwan, and Jiang Li. "Flood Detection Using Multi-Modal and Multi-Temporal Images: A Comparative Study." Remote Sensing 12, no. 15 (July 30, 2020): 2455. http://dx.doi.org/10.3390/rs12152455.
Повний текст джерелаLi, Xiong, Yangping Qiu, Juan Zhou, and Ziruo Xie. "Applications and Challenges of Machine Learning Methods in Alzheimer's Disease Multi-Source Data Analysis." Current Genomics 22, no. 8 (December 2021): 564–82. http://dx.doi.org/10.2174/1389202923666211216163049.
Повний текст джерелаDoan, H. G., and N. T. Nguyen. "Fusion Machine Learning Strategies for Multi-modal Sensor-based Hand Gesture Recognition." Engineering, Technology & Applied Science Research 12, no. 3 (June 6, 2022): 8628–33. http://dx.doi.org/10.48084/etasr.4913.
Повний текст джерелаПаршин, А. И., М. Н. Аралов, В. Ф. Барабанов, and Н. И. Гребенникова. "RANDOM MULTI-MODAL DEEP LEARNING IN THE PROBLEM OF IMAGE RECOGNITION." ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА, no. 4 (October 20, 2021): 21–26. http://dx.doi.org/10.36622/vstu.2021.17.4.003.
Повний текст джерелаIrfan, Bahar, Michael Garcia Ortiz, Natalia Lyubova, and Tony Belpaeme. "Multi-modal Open World User Identification." ACM Transactions on Human-Robot Interaction 11, no. 1 (March 31, 2022): 1–50. http://dx.doi.org/10.1145/3477963.
Повний текст джерелаBelfedhal, Alaa Eddine. "Multi-Modal Deep Learning for Effective Malicious Webpage Detection." Revue d'Intelligence Artificielle 37, no. 4 (August 31, 2023): 1005–13. http://dx.doi.org/10.18280/ria.370422.
Повний текст джерелаToda, Kanon, Kazuya Kishizawa, Yuma Toyoda, Kohei Noda, Heeyoung Lee, Kentaro Nakamura, Koichi Ichige, and Yosuke Mizuno. "Characterization of modal interference in multi-core polymer optical fibers and its application to temperature sensing." Applied Physics Express 15, no. 7 (June 13, 2022): 072002. http://dx.doi.org/10.35848/1882-0786/ac749e.
Повний текст джерелаMa’sum, Muhammad Anwar, Hadaiq Rolis Sanabila, Petrus Mursanto, and Wisnu Jatmiko. "Clustering versus Incremental Learning Multi-Codebook Fuzzy Neural Network for Multi-Modal Data Classification." Computation 8, no. 1 (January 13, 2020): 6. http://dx.doi.org/10.3390/computation8010006.
Повний текст джерелаWróblewska, Anna, Jacek Dąbrowski, Michał Pastuszak, Andrzej Michałowski, Michał Daniluk, Barbara Rychalska, Mikołaj Wieczorek, and Sylwia Sysko-Romańczuk. "Designing Multi-Modal Embedding Fusion-Based Recommender." Electronics 11, no. 9 (April 27, 2022): 1391. http://dx.doi.org/10.3390/electronics11091391.
Повний текст джерелаXu, Ziqi, Jingwen Zhang, Jacob Greenberg, Madelyn Frumkin, Saad Javeed, Justin K. Zhang, Braeden Benedict, et al. "Predicting Multi-dimensional Surgical Outcomes with Multi-modal Mobile Sensing." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 8, no. 2 (May 13, 2024): 1–30. http://dx.doi.org/10.1145/3659628.
Повний текст джерелаKalyani, BJD, Kopparthi Praneeth Sai, N. M. Deepika, Shaik Shahanaz, and G. Lohitha. "Smart Multi-Model Emotion Recognition System with Deep learning." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 1 (February 6, 2023): 139–44. http://dx.doi.org/10.17762/ijritcc.v11i1.6061.
Повний текст джерелаZhang, Wenyin, Yong Wu, Bo Yang, Shunbo Hu, Liang Wu, and Sahraoui Dhelimd. "Overview of Multi-Modal Brain Tumor MR Image Segmentation." Healthcare 9, no. 8 (August 16, 2021): 1051. http://dx.doi.org/10.3390/healthcare9081051.
Повний текст джерелаJuan, Bao, Tuo Min, Hou Meng Ting, Li Xi Yu, and Wang Qun. "Research on Intelligent Medical Engineering Analysis and Decision Based on Deep Learning." International Journal of Web Services Research 19, no. 1 (January 1, 2022): 1–9. http://dx.doi.org/10.4018/ijwsr.314949.
Повний текст джерелаHuang, Tianhao, Xiaozhi Zhu, and Mo Niu. "An End-to-End Benchmarking Tool for Analyzing the Hardware-Software Implications of Multi-modal DNNs." ACM SIGMETRICS Performance Evaluation Review 51, no. 3 (January 3, 2024): 25–27. http://dx.doi.org/10.1145/3639830.3639841.
Повний текст джерелаLi, Pengpai, Yongmei Hu, and Zhi-Ping Liu. "Prediction of cardiovascular diseases by integrating multi-modal features with machine learning methods." Biomedical Signal Processing and Control 66 (April 2021): 102474. http://dx.doi.org/10.1016/j.bspc.2021.102474.
Повний текст джерелаSammali, Federica, Celine Blank, Tom G. H. Bakkes, Yizhou Huang, Chiara Rabotti, Benedictus C. Schoot, and Massimo Mischi. "Multi-Modal Uterine-Activity Measurements for Prediction of Embryo Implantation by Machine Learning." IEEE Access 9 (2021): 47096–111. http://dx.doi.org/10.1109/access.2021.3067716.
Повний текст джерелаYao, Wenfang, Kejing Yin, William K. Cheung, Jia Liu, and Jing Qin. "DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 15 (March 24, 2024): 16416–24. http://dx.doi.org/10.1609/aaai.v38i15.29578.
Повний текст джерелаMason, Rachel E., Nicholas R. Vaughn, and Gregory P. Asner. "Mapping Buildings across Heterogeneous Landscapes: Machine Learning and Deep Learning Applied to Multi-Modal Remote Sensing Data." Remote Sensing 15, no. 18 (September 6, 2023): 4389. http://dx.doi.org/10.3390/rs15184389.
Повний текст джерелаZhang, Shuyan, Steve Qing Yang Wu, Melissa Hum, Jayakumar Perumal, Ern Yu Tan, Ann Siew Gek Lee, Jinghua Teng, U. S. Dinish, and Malini Olivo. "Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis." RSC Advances 14, no. 5 (2024): 3599–610. http://dx.doi.org/10.1039/d3ra05723b.
Повний текст джерелаGhaffar, M. A. A., T. T. Vu, and T. H. Maul. "MULTI-MODAL REMOTE SENSING DATA FUSION FRAMEWORK." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W2 (July 5, 2017): 85–89. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w2-85-2017.
Повний текст джерелаNaseem, Muhammad Tahir, Haneol Seo, Na-Hyun Kim, and Chan-Su Lee. "Pathological Gait Classification Using Early and Late Fusion of Foot Pressure and Skeleton Data." Applied Sciences 14, no. 2 (January 9, 2024): 558. http://dx.doi.org/10.3390/app14020558.
Повний текст джерелаChopparapu, SaiTeja, and Joseph Beatrice Seventline. "An Efficient Multi-modal Facial Gesture-based Ensemble Classification and Reaction to Sound Framework for Large Video Sequences." Engineering, Technology & Applied Science Research 13, no. 4 (August 9, 2023): 11263–70. http://dx.doi.org/10.48084/etasr.6087.
Повний текст джерелаMa’sum, Muhammad Anwar. "Intelligent Clustering and Dynamic Incremental Learning to Generate Multi-Codebook Fuzzy Neural Network for Multi-Modal Data Classification." Symmetry 12, no. 4 (April 24, 2020): 679. http://dx.doi.org/10.3390/sym12040679.
Повний текст джерелаSen, Atriya, Beckett Sterner, Nico Franz, Caleb Powel, and Nathan Upham. "Combining Machine Learning & Reasoning for Biodiversity Data Intelligence." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 14911–19. http://dx.doi.org/10.1609/aaai.v35i17.17750.
Повний текст джерелаZhang, Xue, Fusen Guo, Tao Chen, Lei Pan, Gleb Beliakov, and Jianzhang Wu. "A Brief Survey of Machine Learning and Deep Learning Techniques for E-Commerce Research." Journal of Theoretical and Applied Electronic Commerce Research 18, no. 4 (December 4, 2023): 2188–216. http://dx.doi.org/10.3390/jtaer18040110.
Повний текст джерелаShangaranarayanee, N. P., V. Aakashbabu, M. Balamurugan, and R. Gokulraj. "Machine Learning Driven Smart Transportation Sharing." Journal of ISMAC 6, no. 1 (March 2024): 1–12. http://dx.doi.org/10.36548/jismac.2024.1.001.
Повний текст джерелаBednarek, Michal, Piotr Kicki, and Krzysztof Walas. "On Robustness of Multi-Modal Fusion—Robotics Perspective." Electronics 9, no. 7 (July 16, 2020): 1152. http://dx.doi.org/10.3390/electronics9071152.
Повний текст джерелаAlthenayan, Albatoul S., Shada A. AlSalamah, Sherin Aly, Thamer Nouh, Bassam Mahboub, Laila Salameh, Metab Alkubeyyer, and Abdulrahman Mirza. "COVID-19 Hierarchical Classification Using a Deep Learning Multi-Modal." Sensors 24, no. 8 (April 20, 2024): 2641. http://dx.doi.org/10.3390/s24082641.
Повний текст джерелаChalumuri, Yekanth Ram, Jacob P. Kimball, Azin Mousavi, Jonathan S. Zia, Christopher Rolfes, Jesse D. Parreira, Omer T. Inan, and Jin-Oh Hahn. "Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals." Sensors 22, no. 4 (February 10, 2022): 1336. http://dx.doi.org/10.3390/s22041336.
Повний текст джерелаJo, Saehan, and Immanuel Trummer. "ThalamusDB: Approximate Query Processing on Multi-Modal Data." Proceedings of the ACM on Management of Data 2, no. 3 (May 29, 2024): 1–26. http://dx.doi.org/10.1145/3654989.
Повний текст джерелаZhang, Jianhua, Zhong Yin, Peng Chen, and Stefano Nichele. "Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review." Information Fusion 59 (July 2020): 103–26. http://dx.doi.org/10.1016/j.inffus.2020.01.011.
Повний текст джерелаMansouri, Nesrin, Daniel Balvay, Omar Zenteno, Caterina Facchin, Thulaciga Yoganathan, Thomas Viel, Joaquin Lopez Herraiz, Bertrand Tavitian, and Mailyn Pérez-Liva. "Machine Learning of Multi-Modal Tumor Imaging Reveals Trajectories of Response to Precision Treatment." Cancers 15, no. 6 (March 14, 2023): 1751. http://dx.doi.org/10.3390/cancers15061751.
Повний текст джерелаUllah, Ubaid, Jeong-Sik Lee, Chang-Hyeon An, Hyeonjin Lee, Su-Yeong Park, Rock-Hyun Baek, and Hyun-Chul Choi. "A Review of Multi-Modal Learning from the Text-Guided Visual Processing Viewpoint." Sensors 22, no. 18 (September 8, 2022): 6816. http://dx.doi.org/10.3390/s22186816.
Повний текст джерелаJiao, Zhuqing, Siwei Chen, Haifeng Shi, and Jia Xu. "Multi-Modal Feature Selection with Feature Correlation and Feature Structure Fusion for MCI and AD Classification." Brain Sciences 12, no. 1 (January 5, 2022): 80. http://dx.doi.org/10.3390/brainsci12010080.
Повний текст джерелаQiu, Chen, Stephan Mandt, and Maja Rudolph. "History Marginalization Improves Forecasting in Variational Recurrent Neural Networks." Entropy 23, no. 12 (November 24, 2021): 1563. http://dx.doi.org/10.3390/e23121563.
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