Design of Human-computer Interaction System Using Gesture Recognition Algorithm from the Perspective of Machine Learning

Li, Jiawei

doi:10.1109/cei52496.2021.9574581

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The advancement of science causes education to advance. A teacher who holds the title of professional teacher should follow the development of science and technology (Li, 2021). Professional development will realize a knowledge-based school, which is an understanding of learning, curriculum and human development including learning styles.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Use of Simulation Technology in Digital Learning Content Development

Siregar,

Rofi’i,

Kamal

et al. 2023

J. Journal International Inspire Education Technology

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Education in the era of globalization that allows no limits to find all information is very easy and effective to do anywhere. By utilizing simulation technology in learning so that you can prepare even better. Of course there are stages that must be followed, such as knowing what positive effects are applied using simulation technology for the development of digital learning content, you have to know the methods with people who are experienced and knowledgeable in the field. By utilizing this technology in the form of digital learning content that is able to create effective and quality learning, so that it can make the next generation superior and competitive. Increasingly sophisticated technology can facilitate human work in all fields, especially in the field of education. Many people are competing to create interactive media, so they can earn from the media they create. This should also receive attention from parties related to the world of education. The method used in this study is a quantitative method by distributing a questionnaire containing 15 statements about this simulation technology for digital learning. The purpose of this research is to optimize the use of simulation technology to enhance digital learning for students so they are able to master the skills to use maximally, creatively and innovatively against this limitless technological development. The conclusion from this study is that technology greatly influences student learning development, one of which is by optimizing the use of simulation technology in digital learning. Students and teachers really get a big positive impact with the presence of this sophisticated tool. The limitation of this research is that researchers only conduct research at the school or madradah level, which in fact they need learning media like this in learning in class, so that the class atmosphere is more conducive and attracts students' attention to learning with focus.

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Section: Introductionmentioning

confidence: 99%

Optimizing the Use of Simulation Technology in Digital Learning Content Development

Siregar,

Rofi’i,

Kamal

et al. 2023

J. Journal International Inspire Education Technology

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“…With the same motion, the angle di erence will harm the accuracy of praise, and the probability of misidenti cation will be high. In the eld of HCI, Li [5], through the basic principle of a nger guessing game, used gesture estimation to e ectively detect the gesture features of joints and applied CNN (a network that is used in image recognition and processing) to plan and process the joint features, which solved the bottleneck problem of the poor effect of gesture image segmentation in different environments. Among gesture-based HCI technologies, the essential thing is GR.…”

Section: Introductionmentioning

confidence: 99%

A Novel Deep Learning Technique for Higher Education System

Tang¹,

Liu

2022

Mathematical Problems in Engineering

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This study aims to enhance the interest of university classrooms and the learning efficiency of students. From deep learning, gesture recognition algorithms (GRA) and long short-term memory (LSTM) are adopted to build prediction modules. After the system process is completed, a brand-new human-computer interaction (HCI) system is established. The deep learning GRA augments the operation of the recognition algorithm of the pattern matching method created on the previous image segmentation. Its enticements on two merits of gesture estimation are as follows: rapid detection of gesture joint features and convolutional neural network (CNN) image classification, thereby improving GRA. The recognition rates of “take”, “pinch”, and “point” are 98.6%, 99.5%, and 99.4%, respectively. When the data volume of the LSTM network model is less than 10, the prediction accuracy can reach 70%, and the performance is relatively stable. The designed HCI system can better recognize the teacher’s gesture intent in teaching, execute gesture commands, and optimize the interactive teaching method between the teacher and the computer. This system is a derivative form of gamification teaching. While it improves the interest in teaching, it is also of great significance for improving the teaching efficiency of general higher education.

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