Customizable embedded processor array for multimedia applications

Tükel, Mehmet; Yurdakul, Arda; Örs, Berna

doi:10.1016/j.vlsi.2017.09.009

Cited by 3 publications

(2 citation statements)

References 24 publications

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“…The application of digital multimedia and the diverse application and reuse of multimedia resources in universities show its great potential value (Zhu et al, 2019). The establishment of a university multimedia teaching information management system is the ultimate goal of this research, to make multimedia information data orderly and easy to find and to effectively realize the functions of organization, storage, retrieval and query of multimedia data, especially those complex unformatted data, such as images, audio, video, and animation (Tukel et al, 2018).…”

Section: Multimedia Information System Of Physical Education In Socio...mentioning

confidence: 99%

Research on the Application of Multimedia Image Processing Technology in Sports Sociology Education

2024

International Journal of Web-Based Learning and Teaching Technologies

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In order to cope with sports events, it is difficult for cameras to accurately extract exciting moments during the competition. This article constructs a multimedia information system for sports sociology education. In terms of methodology, low-density architectures are used to measure and encode sparse signals, and the signal is reconstructed at the receiving end. By calculating the marginal probability distribution of each variable node, the reconstructed image is obtained. The experimental results show that this method performs well in detecting lens mutations and gradients, with a higher recall rate than other algorithms. The accuracy, recall rate, and F-value indicators have significantly improved, reaching 6.328%, 4.27%, and 6.012%, respectively. This method is superior to existing game shot extraction methods and lays the foundation for further detecting exciting events in sports competitions. In summary, this study has important guiding significance for the application of multimedia image processing technology in the field of sports sociology education.

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Section: Multimedia Information System Of Physical Education In Socio...mentioning

confidence: 99%

Research on the Application of Multimedia Image Processing Technology in Sports Sociology Education

2024

International Journal of Web-Based Learning and Teaching Technologies

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“…e hardware architectures for wearable visual sensors and portable imaging devices in the IoT and wireless multimedia sensor networks should require minimal hardware resources and consume low energy for a small form factor and long battery life [44,45]. Generally, the computational capabilities of visual sensor nodes have been increasing in recent years [46].…”

Section: Motivationmentioning

confidence: 99%

Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors

Tausif

Khan

Hasan

et al. 2020

Advances in Multimedia

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This paper proposes and evaluates the LFrWF, a novel lifting-based architecture to compute the discrete wavelet transform (DWT) of images using the fractional wavelet filter (FrWF). In order to reduce the memory requirement of the proposed architecture, only one image line is read into a buffer at a time. Aside from an LFrWF version with multipliers, i.e., the LFr WF m , we develop a multiplier-less LFrWF version, i.e., the LFr WF ml , which reduces the critical path delay (CPD) to the delay T a of an adder. The proposed LFr WF m and LFr WF ml architectures are compared in terms of the required adders, multipliers, memory, and critical path delay with state-of-the-art DWT architectures. Moreover, the proposed LFr WF m and LFr WF ml architectures, along with the state-of-the-art FrWF architectures (with multipliers (Fr WF m ) and without multipliers (Fr WF ml )) are compared through implementation on the same FPGA board. The LFr WF m requires 22% less look-up tables (LUT), 34% less flip-flops (FF), and 50% less compute cycles (CC) and consumes 65% less energy than the Fr WF m . Also, the proposed LFr WF ml architecture requires 50% less CC and consumes 43% less energy than the Fr WF ml . Thus, the proposed LFr WF m and LFr WF ml architectures appear suitable for computing the DWT of images on wearable sensors.

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PulseDL: A reconfigurable deep learning array processor dedicated to pulse characterization for high energy physics detectors

Wang

Fan

et al. 2020

Nuclear Instruments and Methods in Physics Research Section A:

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Customizable embedded processor array for multimedia applications

Cited by 3 publications

References 24 publications

Research on the Application of Multimedia Image Processing Technology in Sports Sociology Education

Research on the Application of Multimedia Image Processing Technology in Sports Sociology Education

Lifting-Based Fractional Wavelet Filter: Energy-Efficient DWT Architecture for Low-Cost Wearable Sensors

PulseDL: A reconfigurable deep learning array processor dedicated to pulse characterization for high energy physics detectors

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