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Rinat Khusainov
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2020 – today
- 2024
- [c18]Sven Glatzer, Stavros Shiaeles, Rinat Khusainov
, Rahim Taheri
Peer-to-Peer Meets Onion: The Veilid Framework. CSR 2024: 1-6 - [c17]Gelayol Golcarenarenji, Rinat Khusainov, Alexander E. Gegov, Ignacio Martinez-Alpiste:
Detecting Violent Behaviour on Edge Using Convolutional Neural Networks. IS 2024: 1-6 - 2022
- [c16]Benjamin Aziz, Aysha Bukhelli, Rinat Khusainov
A Novel Method for Embedding and Extracting Secret Messages in Textual Documents based on Paragraph Resizing. SECRYPT 2022: 714-719 - 2021
- [c15]Omar Ali
Light Syntax Parsing and Fuzzy Systems for Rhetorical Structure Theory Text Segmentation. INISTA 2021: 1-6 - 2020
- [c14]Omar Ali
Conventional and Structure Based Sentiment Analysis: A Survey. IJCNN 2020: 1-8
2010 – 2019
- 2018
- [c13]Lining Zhang, Rinat Khusainov, John Chiverton:
Practical Action Recognition with Manifold Regularized Sparse Representations. BMVC 2018: 315 - [c12]David A. Sanders
Sharing Driving Between a Vehicle Driver and a Sensor System Using Trust-Factors to Set Control Gains. IntelliSys (1) 2018: 1182-1195 - 2016
- [c11]David Adrian Sanders
Introducing dead bands within two-dimensional clusters of user data to improve data classification. HSI 2016: 14-20 - [c10]Mohamad Al-Wattar, Rinat Khusainov
Activity Recognition from Video Data Using Spatial and Temporal Features. Intelligent Environments 2016: 250-253 - 2015
- [j4]Mohamed Al-Mosawi, Rinat Khusainov
Rain granularity effects on bandwidth demand for faded DVB-RCS systems. Int. J. Satell. Commun. Netw. 33(3): 241-257 (2015) - 2014
- [j3]Sebastian D. Bersch, Djamel Azzi, Rinat Khusainov
Sensor Data Acquisition and Processing Parameters for Human Activity Classification. Sensors 14(3): 4239-4270 (2014) - [c9]Sebastian D. Bersch, Djamel Azzi, Rinat Khusainov, Ifeyinwa E. Achumba:
A Open Hardware Wireless Sensor Monitoring System for Human Wellbeing Research in Ambient Assisted Living. S-CUBE 2014: 30-40 - [c8]Sebastian D. Bersch, Djamel Azzi, Rinat Khusainov
Artificial Immune System - A New Approach for the Long-Term Data Monitoring in Ambient Assisted Living. S-CUBE 2014: 41-50 - 2013
- [j2]Sebastian D. Bersch, Djamel Azzi, Rinat Khusainov
Artificial Immune Systems for Anomaly Detection in Ambient Assisted Living Applications. Int. J. Ambient Comput. Intell. 5(3): 1-15 (2013) - [j1]Rinat Khusainov
Real-Time Human Ambulation, Activity, and Physiological Monitoring: Taxonomy of Issues, Techniques, Applications, Challenges and Limitations. Sensors 13(10): 12852-12902 (2013) - 2012
- [c7]Ifeyinwa E. Achumba, Sebastin Bersch, Rinat Khusainov, Djamel Azzi, Ugochukwu Kamalu:
On time series sensor data segmentation for fall and activity classification. Healthcom 2012: 427-430 - 2011
- [c6]Sebastian D. Bersch, Djamel Azzi, Rinat Khusainov:
Fall Detection using Biologially Inspired Monitoring - Artificial Immune System in the Area of Assisted Living. IJCCI (ECTA-FCTA) 2011: 320-323 - [c5]Sebastian D. Bersch, Christian M. J. Chislett, Djamel Azzi, Rinat Khusainov, Jim S. Briggs
Activity detection using frequency analysis and off-the-shelf devices: Fall detection from accelerometer data. PervasiveHealth 2011: 362-365
2000 – 2009
- 2009
- [c4]Taiwo Ayodele, Shikun Zhou, Rinat Khusainov:
Email Grouping and Summarization: An Unsupervised Learning Technique. CSIE (5) 2009: 575-579 - [c3]Taiwo Ayodele, Shikun Zhou
Email Reply Prediction: A Machine Learning Approach. HCI (9) 2009: 114-123 - [c2]Taiwo Ayodele, Shikun Zhou
Email classification: Solution with back propagation technique. ICITST 2009: 1-6 - [c1]Taiwo Ayodele, Shikun Zhou
Intelligent email prediction system (IEPS). ICITST 2009: 1-5
Coauthor Index
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