Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

Manikandan, S.; Chinnadurai, M.

doi:10.1007/s11277-021-08081-3

Cited by 42 publications

(23 citation statements)

References 17 publications

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“…The Computer Vision community has been interested in problems pertaining to sports for a long while. There have been numerous applications in various sports, like cricket [14], soccer [15], volleyball [16], basketball [17], tennis [18], badminton [19] and hockey [20] among other sports. Moreover, sports have emerged as a popular proxy task for evaluating computer vision algorithms due to complex nature of most sports.…”

Section: Related Workmentioning

confidence: 99%

Ball and Player Detection & Tracking in Soccer Videos Using Improved YOLOV3 Model

Naik

Hashmi

2021

Preprint

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Over the past few years, there has been a tremendous increase in the interest and enthusiasm for sports among people. This has led to an increase in the importance given to video recording of various sports that capture even the minutest detail using high-end equipment. Recording and analysis have thereby become extremely crucial in sports like soccer that involve several complex and fast events. Ball detection and tracking along with player analysis have emerged as an area of interest among a lot of analysts and researchers. This is because it helps coaches in performance assessment of the team and in decision making to obtain optimized results. Video analysis can additionally be used by coaches and recruiters to look for new, talented players based on their previously played games. Ball detection also plays a pivotal role in assisting the referees in making decisions at game-changing moments. However, as the ball is almost always moving, its shape-appearance keeps changing over time and it is frequently occluded by players, it makes it difficult to track it throughout the game. We propose a deep learning-based YOLOv3 model for the ball and player detection in broadcast soccer videos. Initially, the videos are processed and unnecessary parts like zoom-ins, replays, etc., are removed to obtain only the relevant frames from each game. Tracking is achieved using the SORT algorithm which employs a Kalman filtering and bounding box overlap.

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Section: Related Workmentioning

confidence: 99%

Ball and Player Detection & Tracking in Soccer Videos Using Improved YOLOV3 Model

Naik

Hashmi

2021

Preprint

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“…Therefore, deep learning techniques [14][15][16] are utilized in the speech synthesis process to successfully analyze the high-dimensional data that extracts the high-level information. Due to the effective analysis, learning process, and easily adaption characteristics, deep learning techniques incorporate the different neural network types.…”

Section: Background Studymentioning

confidence: 99%

Creating Speech Synthesis Process by Using Pulse Model in Log-Domain Vocoder With Whale Optimized Deep Convolution Neural Networks

Radha¹,

Vijayalakshmi²

2021

Preprint

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Speech synthesis is an artificial production of human speech by utilizing computer systems called a speech synthesizer. Several statistical parameters are used in previous works to perform the speech synthesis process, but the vocoder is combined only the simpler model. Due to the lack of sequence of modeling, the quality degrading process is reducing the speech synthesis. Therefore, the Pulse model in log-domain vocoder with whale optimized deep convolution recurrent neural network is applied to investing the vocoder in this work. During this analysis, Mel-Generalized Cepstrum (MGC), maximum voice frequency (MVF), and F0 are applied to processing the signal to extracting the features, and the vocoder is generated successfully. The system's effectiveness is then evaluated using experimental results compared to deep neural networks and traditional recurrent networks.

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“…Moreover, Toyota Research Institute referred to that no one in the company organization organisation is even shut to mission diploma 5 automation [42]. Fatalities [9], [10] delivered on through potential of capability of Genius of immature technological records undermine public acceptance of ADSs. According to a latest survey [34], the majority of customers query the protection of the technology, and pick out a surprisingly desirable extent of manipulate over the enchantment and use of ADS.…”

Section: Pedestrian Detectionmentioning

confidence: 99%

SLAM – DATMO Method for an Autonomous Vehicles

Vasudevan

2021

Preprint

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Automated automobiles navigate US highways and many different countries round the world. Current question is about AVs revolve round whether or not such applied sciences have to or need to be implemented; they are already with us. Rather, such questions are more and more established on how such utilized sciences will have an impact on evolving transportation systems. More importantly, how will mobility itself exchange as these impartial operational automobiles first share and then dominate our roadways? How will the public be saved apprised of their evolving capacities? We seem right here to tackle these problems and to furnish some recommendations for the issues that are presently emerging.

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Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

Cited by 42 publications

References 17 publications

Ball and Player Detection & Tracking in Soccer Videos Using Improved YOLOV3 Model

Ball and Player Detection & Tracking in Soccer Videos Using Improved YOLOV3 Model

Creating Speech Synthesis Process by Using Pulse Model in Log-Domain Vocoder With Whale Optimized Deep Convolution Neural Networks

SLAM – DATMO Method for an Autonomous Vehicles

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Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

Cited by 42 publications

References 17 publications

Ball and Player Detection &amp; Tracking in Soccer Videos Using Improved YOLOV3 Model

Ball and Player Detection &amp; Tracking in Soccer Videos Using Improved YOLOV3 Model

Creating Speech Synthesis Process by Using Pulse Model in Log-Domain Vocoder With Whale Optimized Deep Convolution Neural Networks

SLAM – DATMO Method for an Autonomous Vehicles

Contact Info

Product

Resources

About

Ball and Player Detection & Tracking in Soccer Videos Using Improved YOLOV3 Model

Ball and Player Detection & Tracking in Soccer Videos Using Improved YOLOV3 Model