Intelligent Human Computer Interface Devices based on Neural Network
DOI:
https://doi.org/10.64882/ijrt.v13.i4.436Keywords:
Human Computer, Intelligent Interaction, Anti-spoofing Detection, Machine LearningAbstract
Intelligent solutions based on artificial intelligence (AI) techniques, algorithms, and sensor technologies are needed to give computers human communication abilities and to allow for organic human-computer interaction. In order to investigate trends in human–computer intelligent interaction (HCII) research, classify the available evidence, and determine possible avenues for future investigation, this study sought to identify and analyze the most advanced AI techniques, algorithms, and sensor technologies in the body of existing HCII research. We map the corpus of research on HCII in a methodical manner. Intelligent emotion, gesture, and facial expression identification, false news, and face anti-spoofing detection have been the main areas of study in the HCII domains. This research examines face anti-spoofing detection based on HCII utilizing various machine learning techniques.
References
Jarosz, M.; Nawrocki, P.; Śnieżyński, B.; Indurkhya, B. Multi-Platform Intelligent System for Multimodal Human- Computer Interaction. Comput. Inform. 2021, 40, 83– 103.
Prathiba, T.; Kumari, R.S.S. Content based video retrieval system based on multimodal feature grouping by KFCM clustering algorithm to promote human–computer interaction. J. Ambient. Intell. Humaniz. Comput. 2021, 12, 6215–6229.
Ince, G.; Yorganci, R.; Ozkul, A.; Duman, T.B.; Köse, H. An audiovisual interface-based drumming system for multimodal human–robot interaction. J. Multimodal User Interfaces 2020, 15, 413–428.
Wu, D.; Zhang, J.; Zhao, Q. Multimodal Fused Emotion Recognition About Expression-EEG Interaction and Collaboration Using Deep Learning. IEEE Access 2020, 8, 133180–133189.
Mosquera-DeLaCruz, J.H.; Loaiza-Correa, H.; Nope- Rodríguez, S.E.; Restrepo-Girón, A.D. Human-computer multimodal interface to internet navigation. Disabil. Rehabil. Assist. Technol. 2021, 16, 807–820.
Nayak, S.; Nagesh, B.; Routray, A.; Sarma, M. A Human– Computer Interaction framework for emotion recognition through time-series thermal video sequences. Comput. Electr. Eng. 2021, 93, 107280.
Liu, X.; Zhang, L. Design and Implementation of Human- Computer Interaction Adjustment in Nuclear Power Monitoring System. Mi-croprocessors and Microsystems. Microprocess. Microsyst. 2021, 104096.
Dybvik, H.; Erichsen, C.K.; Steinert, M. Demonstrating the feasibility of multimodal neuroimaging data capture with a wearable electoencephalography + functional near- infrared spectroscopy (eeg+fnirs) in situ. Proc. Des. Soc. 2021, 1, 901–910.
Iio, T.; Yoshikawa, Y.; Chiba, M.; Asami, T.; Isoda, Y.; Ishiguro, H. Twin-Robot Dialogue System with Robustness against Speech Recognition Failure in Human- Robot Dialogue with Elderly People. Appl. Sci. 2020, 10, 1522.
Robert, L.P., Jr.; Bansal, G.; Lütge, C. ICIS 2019 SIGHCI workshop panel report: Human–computer interaction challenges and opportunities for fair, trustworthy and ethical artificial intelligence. AIS Trans. Hum.-Comput. Interact. 2020, 12, 96–108.
Cao, Y.; Geddes, T.A.; Yang, J.Y.H.; Yang, P. Ensemble deep learning in bioinformatics. Nat. Mach. Intell. 2020, 2, 500–508.
Panwar, H.; Gupta, P.; Siddiqui, M.K.; Morales- Menendez, R.; Singh, V. Application of deep learning for
fast detection of COVID-19 in X-rays using nCOVnet. Chaos Solitons Fractals 2020, 138, 109944.
Shen, C.-W.; Luong, T.-H.; Ho, J.-T.; Djailani, I. Social media marketing of IT service companies: Analysis using a concept-linking mining approach. Ind. Mark. Manag. 2019, 90, 593–604.
Duan, H.; Sun, Y.; Cheng, W.; Jiang, D.; Yun, J.; Liu, Y.; Liu, Y.; Zhou, D. Gesture recognition based on multi- modal feature weight. Concurr. Comput. Pract. Exp. 2021, 33, e5991.
Gurcan, F.; Cagiltay, N.E.; Cagiltay, K. Mapping Human– Computer Interaction Research Themes and Trends from Its Existence to Today: A Topic Modeling-Based Review of past 60 Years. Int. J. Hum.-Comput. Interact. 2021, 37, 267–280.
Downloads
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
