Current Issue : January-March Volume : 2023 Issue Number : 1 Articles : 5 Articles
Aerobics sports injury diagnosis is a rapid diagnosis of sports injuries caused by athletes in the process of aerobics training or competition. The purpose of this paper is to use image processing technology to study and analyze the diagnosis of aerobics sports injury, so that the diagnosis results can be obtained more quickly and effectively. This paper first introduces the image processing technology and then analyzes the sports injury in colleges and universities. Firstly, the algorithm formula of image processing technology is given, and then the algorithm is introduced into the dynamic analysis of aerobics injury diagnosis. The two are compared through example analysis. The experimental results show that joint strain, sprains, and muscle strain are the main types of sports injury of College Aerobics students, reaching 59, 50, and 31 times, respectively. When using image processing technology in the diagnosis of sports injury, the diagnosis results can be obtained quickly and effectively....
With the hot development of football, sports injuries caused by football have also received special attention. In football games, although there are medical staff on and off the field always on call to protect the safety of players, because of the complexity of diagnosis work, medical staff can easily lead to diagnostic errors due to factors such as fatigue, which seriously affects the condition of athletes. Image processing is a technology that uses computer to process images, which can greatly overcome the uncertain factors brought by manual diagnosis. Based on this, this paper uses image processing technology and pattern recognition as technical means to explore the specific application of image processing in football injury diagnosis. This paper firstly takes football clubs as the main research object and analyzes and explores the specific utility of image segmentation and feature recognition in sports injury image processing. Then, starting from the relevant image features, the paper analyzes and compares the sensitivity of support vector machine pattern recognition and neural network pattern recognition in football injury diagnosis. This article comprehensively summarizes the application of image processing technology in the diagnosis of football injuries and puts forward constructive suggestions for its subsequent development. Experiments show that the effect of pattern recognition is often different for different injury parts of football. Among them, the sensitivity of pattern recognition based on image processing can reach 68.9%, and the detection rate of football injuries can also be maintained at about 81.2%. This fully shows that image processing technology can play an active role in the actual football injury diagnosis, and provide very valuable information for clinical diagnosis....
Coronavirus disease 2019 (COVID-19) has a significant impact on human life. The novel pandemic forced humans to change their lifestyles. Scientists have broken through the vaccine in many countries, but the face mask is the only protection for public interaction. In this study, deep neural networks (DNN) have been employed to determine the persons wearing masks correctly. The faster region-based convolutional neural networks (RCNN) model has been used to train the data using graphics processing unit (GPU) device. To achieve our goals, we used a multiphase detection model: first, to label the face mask, and second to detect the edge and compute edge projection for the chosen face region within the face mask. The current findings revealed that faster RCNN was efficient and precise, giving 97% accuracy. The overall loss after 200,000 epochs is 0.0503, with a trend to decrease. While the loss is falling, we are getting more accurate results. As a result, the faster RCNN technique effectively identifies whether a person is wearing face masks or not, and the training period was decreased with better accuracy. In the future, Deep Neural Network (DNN) might be used first to train the data and then compress the dimensions of the input to run it on low-powered devices, resulting in a lower computational cost. Our proposed system can achieve high face detection accuracy and coarsely obtain face posture estimation based on the specified rule. The faster RCNN learning algorithm returns high precision, and the model’s lower computational cost is achieved on GPU. We use the “label-image” application to label the photographs extracted from the dataset and apply Inception V2 of faster RCNN for face mask detection and classification....
In order to further improve the problems of poor rationality and weak antinoise ability of existing image processing algorithms and technical algorithms, an image processing research method based on fuzzy mathematical theory is proposed. First, aiming at the ill-posed problem of the PFCM algorithm, the neutrality and rejection degree are used to construct a regular term and embed the algorithm objective function to enhance the correlation between the attribute parameters of the fuzzy set of the sample graph, so as to solve the ill-posed problem of the PFCM algorithm. Secondly, in view of the same noise sensitivity problem of PFCM algorithm as a traditional fuzzy clustering algorithm, combined with the robust ideas of FCM_S1 and FCM_S2 algorithms, the objective function of robust segmentation algorithm for graph fuzzy clustering (RPFCM_s) is constructed. The misclassification rate of the clustering algorithm proposed in this study in image segmentation is reduced by 38%–76%, and the misclassification rate of the corresponding segmentation result of the ATPFCA algorithm is reduced by 5%–77%. Therefore, the algorithm not only improves the effective segmentation efficiency of the fuzzy mathematical theory algorithm for the processing of uneven grayscale images but also enhances the anti-noise robustness of the algorithm....
In the extensive age, dear designate perplexity and relatively supercilious show charge in the traditive parcel extend project composition, the double discriminator GAN is ply to the bale work indicate composition. On the basis of BicycleGAN, a topic discriminator is added, and the analogous privation sine and external province are reformed. In the proof, the input aim is a likeness suit of “margin idol + source cast,” and the product goal is the copy with the top 10 chance of genuineness. The trial arise are appraised from the three aspects of variegation, PSNR importance, and SSIM appraise.Thearise shows that the effigy produced by the double discriminator GAN not only has improved variegation but also better peculiarity of show lowdown. Therefore, it is practicable to devote the double discriminator GAN to the look sketch of parcel products. On the one side, it can stipulate designers with sketch breath, and on the other side, it can also rescue manpower and significant cause and disapprove duty ability....
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