With the continuously increasing competition in the modern society, the learning pressure of students is getting greater and greater and many students are in shortage of reasonable time to take physical exercises so t...With the continuously increasing competition in the modern society, the learning pressure of students is getting greater and greater and many students are in shortage of reasonable time to take physical exercises so that they are in a state of sub-health for a long time. Aerobics, as a combination of music and sports, has been more and more popular among teachers and students. However, in aerobics training, the injuries to the physical bodies of students will be caused due to the improper training methods. Therefore, in this paper, the points needing attention in aerobics training is studied, and then scientific aerobics training methods are proposed.展开更多
Recent days,Image retrieval has become a tedious process as the image database has grown very larger.The introduction of Machine Learning(ML)and Deep Learning(DL)made this process more comfortable.In these,the pair-wi...Recent days,Image retrieval has become a tedious process as the image database has grown very larger.The introduction of Machine Learning(ML)and Deep Learning(DL)made this process more comfortable.In these,the pair-wise label similarity is used tofind the matching images from the database.But this method lacks of limited propose code and weak execution of misclassified images.In order to get-rid of the above problem,a novel triplet based label that incorporates context-spatial similarity measure is proposed.A Point Attention Based Triplet Network(PABTN)is introduced to study propose code that gives maximum discriminative ability.To improve the performance of ranking,a corre-lating resolutions for the classification,triplet labels based onfindings,a spatial-attention mechanism and Region Of Interest(ROI)and small trial information loss containing a new triplet cross-entropy loss are used.From the experimental results,it is shown that the proposed technique exhibits better results in terms of mean Reciprocal Rank(mRR)and mean Average Precision(mAP)in the CIFAR-10 and NUS-WIPE datasets.展开更多
文摘With the continuously increasing competition in the modern society, the learning pressure of students is getting greater and greater and many students are in shortage of reasonable time to take physical exercises so that they are in a state of sub-health for a long time. Aerobics, as a combination of music and sports, has been more and more popular among teachers and students. However, in aerobics training, the injuries to the physical bodies of students will be caused due to the improper training methods. Therefore, in this paper, the points needing attention in aerobics training is studied, and then scientific aerobics training methods are proposed.
文摘Recent days,Image retrieval has become a tedious process as the image database has grown very larger.The introduction of Machine Learning(ML)and Deep Learning(DL)made this process more comfortable.In these,the pair-wise label similarity is used tofind the matching images from the database.But this method lacks of limited propose code and weak execution of misclassified images.In order to get-rid of the above problem,a novel triplet based label that incorporates context-spatial similarity measure is proposed.A Point Attention Based Triplet Network(PABTN)is introduced to study propose code that gives maximum discriminative ability.To improve the performance of ranking,a corre-lating resolutions for the classification,triplet labels based onfindings,a spatial-attention mechanism and Region Of Interest(ROI)and small trial information loss containing a new triplet cross-entropy loss are used.From the experimental results,it is shown that the proposed technique exhibits better results in terms of mean Reciprocal Rank(mRR)and mean Average Precision(mAP)in the CIFAR-10 and NUS-WIPE datasets.
