No‐reference video quality assessment method based on spatio‐temporal features using the ELM algorithm

Silva, Wyllian Bezerra da; Mikowski, Alexandre; Casali, Rafael Machado

doi:10.1049/iet-ipr.2019.0941

Cited by 9 publications

(3 citation statements)

References 31 publications

(40 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the increasing maturity of the deep learning field, various deep learning algorithms have emerged, among which the ELM algorithm is widely used in various fields because of its high accuracy and running speed. The improved model was found to be significantly more accurate than the original model, and the model was shown to be practically applicable to video quality monitoring systems [7]. To address the issues of large storage capacity, high void probability, and insufficient integrity of the guiding catalogues in stellar sensors, Zhu et al proposed a large field-of-view stellar sensor model combining the spherical spiral method and ELM [8].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Application of ELM Algorithm Incorporating AE Principles in Wireless Communication Signal Detection

Zhao,

Yu,

Feng

2023

IEEE Access

View full text Add to dashboard Cite

With the development of society, the requirements for communication are getting higher and higher, but the detection performance of wireless communication signals is insufficient. To solve this problem, this paper combines the principle of Auto-encoder (AE) and the feature classification function of Extreme Learning Machine (ELM) algorithm to obtain AE-ELM algorithm, and builds a new wireless communication signal detection model based on this algorithm, hoping to improve the detection performance of wireless communication signals. The performance comparison experiment of the proposed AE-ELM algorithm shows that the bit error rate and average relative time complexity of the algorithm are 0.0004 and 0.5292s respectively, which is better than the comparison algorithm. Additionally, the effectiveness of the fusion algorithm-based signal detection model for wireless communication is investigated, and the findings demonstrate that this model outperforms the others with the lowest detection error rate of 0.0031. The above results demonstrate the high application potential of the novel wireless communication signal detection model and its ability to significantly improve the performance of wireless communication signal detection. Its application to wireless communication signal detection can greatly promote the development of the signal detection field in China.

show abstract

Section: Related Workmentioning

confidence: 99%

“…In equation (7), L is the number of neurons in the hidden layer. The output value of the j th hidden layer node for the training sample n…”

Section: { }mentioning

confidence: 99%

Application of ELM Algorithm Incorporating AE Principles in Wireless Communication Signal Detection

Zhao,

Yu,

Feng

2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Robustness is a very important characteristic in the research of motion video compression algorithms. It not only affects the data processing process, but also determines its algorithm performance [1][2]. For example, when the number of real-time sequences input is small, it can be considered that the frame image is relatively complete.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Motion Teaching Video Compression Algorithm Based on Artificial Intelligence

2023

IJECMR

View full text Add to dashboard Cite

Sports are a common activity of human beings, and their development levels vary in different fields. With the continuous progress of science and technology and the increasing level of computer technology, many new algorithms have emerged. This article mainly studied the method and implementation principle of Motion Teaching Video Compression (MTVC) based on artificial intelligence, and verified through MATLAB language simulation experiments the problems and improvement measures in the storage, processing, and output result analysis of commonly used data under the applicable parameters of this control strategy. Finally, the functionality of the algorithm model was tested. The test results showed that the compression ratio of the system was above 85%. The video clarity was very high, and the video bitrate was above 720kbps. The video decoding time was within 3 to 5 seconds. This could improve the compression effect of traditional sports teaching videos and enhance students' interest in learning.

show abstract

Evaluation Method of Oral English Digital Teaching Quality Based on Decision Tree Algorithm

Zhou

2022

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

View full text Add to dashboard Cite

No‐reference video quality assessment method based on spatio‐temporal features using the ELM algorithm

Cited by 9 publications

References 31 publications

Application of ELM Algorithm Incorporating AE Principles in Wireless Communication Signal Detection

Application of ELM Algorithm Incorporating AE Principles in Wireless Communication Signal Detection

Investigation on Motion Teaching Video Compression Algorithm Based on Artificial Intelligence

Evaluation Method of Oral English Digital Teaching Quality Based on Decision Tree Algorithm

Contact Info

Product

Resources

About