RETRACTED: Research on noise impact of building environment based on FPGA high-performance algorithm

Wu, Jian; Xu, Jiming

doi:10.1016/j.micpro.2020.103342

Cited by 7 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 7(a) is the AP of the model in the target detection category from Aeroplane to Dining table, and Figure 7 e latest research algorithm [26][27][28] is compared with the algorithm proposed in Figure 8. Figure 7(a) shows the accuracy of different models on different datasets, and Figure 7(b) shows the recall of different models on different datasets.…”

Section: Results Analysismentioning

confidence: 99%

[Retracted] Adoption of Convolutional Neural Network Algorithm Combined with Augmented Reality in Building Data Visualization and Intelligent Detection

Wei

Tang

et al. 2021

Complexity

View full text Add to dashboard Cite

It aims to improve the degree of visualization of building data, ensure the ability of intelligent detection, and effectively solve the problems encountered in building data processing. Convolutional neural network and augmented reality technology are adopted, and a building visualization model based on convolutional neural network and augmented reality is proposed. The performance of the proposed algorithm is further confirmed by performance verification on public datasets. It is found that the building target detection model based on convolutional neural network and augmented reality has obvious advantages in algorithm complexity and recognition accuracy. It is 25 percent more accurate than the latest model. The model can make full use of mobile computing resources, avoid network delay and dependence, and guarantee the real-time requirement of data processing. Moreover, the model can also well realize the augmented reality navigation and interaction effect of buildings in outdoor scenes. To sum up, this study provides a research idea for the identification, data processing, and intelligent detection of urban buildings.

show abstract

Section: Results Analysismentioning

confidence: 99%

[Retracted] Adoption of Convolutional Neural Network Algorithm Combined with Augmented Reality in Building Data Visualization and Intelligent Detection

Wei

Tang

et al. 2021

Complexity

View full text Add to dashboard Cite

show abstract

“…In the further view, Verilog HDL (Hardware Description Language) gives new opportunities to the users based on high level design paths. Therefore, behavioral view of the desired filter architecture can be safely transformed into block level synthesis, which will be resulted in transistor level design by adding pads and clock trees [12][13].…”

Section: Figurementioning

confidence: 99%

A Reconfigurable 4th Order IIR Filter For The Low Frequency Applications

ÖZENLİ

2023

Mühendislik Bilimleri Ve Araştırmaları Dergisi

View full text Add to dashboard Cite

Huge numbers of advanced electrical engineering applications employ infinite impulse response (IIR) filters very frequently in order to meet market’s demands. Especially, some applications such as video processing, digital signal processing and high-speed digital communication necessitate computational efficiency and low latency. In this point of view, high-speed processing of digital data require a digital signal processor or an FPGA instead of a conventional microprocessor. In this respect, in the last decades, FPGAs are commonly used in order to bring new opportunities to the designers. This work gives a FPGA hardware design of a 4th order IIR reconfigurable filter structure. The proposed filter’s maximum clock frequency is around 32MHz which covers different low frequency applications from biomedical signal processing up to speech applications. To verify the performance of the filter, 4th order Butterworth and Chebyshev filters are realized in the basis of Matlab results and FPGA behavioral model. Also, consuming logic gates and blocks are given in order to evaluate chip area occupation. It should be considered that the proposed filter scheme presents promising results to meet low frequency applications.

show abstract

Digital Twin framework for automated fault source detection and prediction for comfort performance evaluation of existing non-residential Norwegian buildings

Hosamo

Nielsen

Kraniotis

et al. 2023

Energy and Buildings

View full text Add to dashboard Cite

RETRACTED: Research on noise impact of building environment based on FPGA high-performance algorithm

Cited by 7 publications

References 7 publications

[Retracted] Adoption of Convolutional Neural Network Algorithm Combined with Augmented Reality in Building Data Visualization and Intelligent Detection

[Retracted] Adoption of Convolutional Neural Network Algorithm Combined with Augmented Reality in Building Data Visualization and Intelligent Detection

A Reconfigurable 4th Order IIR Filter For The Low Frequency Applications

Digital Twin framework for automated fault source detection and prediction for comfort performance evaluation of existing non-residential Norwegian buildings

Contact Info

Product

Resources

About