Current Issue : July - September Volume : 2020 Issue Number : 3 Articles : 5 Articles
Nowadays, there has been a rapid increase in the variety and popularity of\nmessaging systems and social networks. It is imperative to consider the effect\nand impact of the number of words feature on the verification process for\nmodern messaging systems such as Twitter, Facebook, SMS and Email. Given\nthe volume of text is often a restricted factor (due to the nature of messaging\nsystems), key to this investigation is a better understanding of what length of\nmessage is required to improve performance...............................
This paper presents a new multisupervised coupled metric learning (MS-CML) method for low-resolution face image matching.\nWhile coupled metric learning has achieved good performance in degraded face recognition, most existing coupled metric\nlearning methods only adopt the category label as supervision, which easily leads to changes in the distribution of samples in the\ncoupled space. And the accuracy of degraded image matching is seriously influenced by these changes. To address this problem, we\npropose an MS-CML method to train the linear and nonlinear metric model, respectively, which can project the different\nresolution face pairs into the same latent feature space, under which the distance of each positive pair is reduced and that of each\nnegative pair is enlarged. In this work, we defined a novel multisupervised objective function, which consists of a main objective\nfunction and an auxiliary objective function. The supervised information of the main objective function is the category label,\nwhich plays a major supervisory role. The supervised information of the auxiliary objective function is the distribution relationship\nof the samples, which plays an auxiliary supervisory role. Under the supervision of category label and distribution\ninformation, the learned model can better deal with the intraclass multimodal problem, and the features obtained in the coupled\nspace are more easily matched correctly. Experimental results on three different face datasets validate the efficacy of the\nproposed method....
Learning is mainly based on the studentsâ?? mental activities. If they can learn spontaneously,\nit will help increase their interest and the effectiveness of the learning. Learning through playing will\nmake it easier for students to learn spontaneously. The balance between gameplay and education in\neducational games is a key issue in designing such games.,.......................
Internet of Multimedia Things (IoMT) brings convenient and intelligent services while also\nbringing huge challenges to multimedia data security and privacy. Access control is used to protect\nthe confidentiality and integrity of restricted resources............................
Digital watermarking has been utilized effectively for copyright protection of multimedia\ncontents. This paper suggests a blind symmetric watermarking algorithm using fan beam transform\n(FBT) and QR decomposition (QRD) for color images..........................
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