In the landscape of data mining applications, the difficult task of manually labeling extensive datasets presents formidable challenges owing to its inherent difficulties, costliness, and time consuming nature. To add...
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ISBN:
(数字)9798350357509
ISBN:
(纸本)9798350357516
In the landscape of data mining applications, the difficult task of manually labeling extensive datasets presents formidable challenges owing to its inherent difficulties, costliness, and time consuming nature. To address the limitations associated with manual labeling, semi-supervised learning emerges as a promising paradigm, harnessing the potential of both Data with and without labels in the course of training. SVM based semi-supervised learning (S3VM), one of the several semi-supervised learning approaches, has shown potential in improving performance of classification. This research paper introduces a novel approach that combine rough sets with SVM based Semi-supervised learning for image classification. This innovative methodology involves employing a Convolutional Neural Network (CNN) model to undergo training on labeled data, make predictions on unlabeled data, and subsequently undergo retraining. Feature extraction is then executed for classification. Following this, Rough Set theory based feature selection technique is used, generating a reduct that functions as a rule for SVM. This comprehensive method not only improves the field of image classification but also offering a novel and pragmatic solution to problems in semi-supervised learning. This procedure concludes in an evaluation of the models final out come using experiments on the CIFAR-10 benchmark dataset, where it achieved an impressive accuracy of 97.30%.
Nowadays, the use of accelerators in high performance computing has become more common than ever before. The most used accelerators must be the Graphics Processing Unit (GPU). It has emerged as an important component ...
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ISBN:
(数字)9798350383454
ISBN:
(纸本)9798350383461
Nowadays, the use of accelerators in high performance computing has become more common than ever before. The most used accelerators must be the Graphics Processing Unit (GPU). It has emerged as an important component in most of the parallel computing scenarios, surpassing the capabilities of the traditional Central Processing Unit (CPU) in perspective of both performance and energy efficiency.
In recent years, due to the proliferation of information and communication technology, as well as AI technology, industrial control systems, which were once in a closed network environment, have also integrated relate...
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information security risk is of utmost importance and a crucial concern, particularly within a clinical laboratory responsible for managing sensitive public health information. Various endeavors have been undertaken b...
information security risk is of utmost importance and a crucial concern, particularly within a clinical laboratory responsible for managing sensitive public health information. Various endeavors have been undertaken by institutions to tackle this pressing challenge effectively. This research seeks to develop a computer-based decision model for assessing information security risks. The model is scientifically constructed using the fuzzy logic method as its core approach and designed through an object-oriented approach. Impressively, the model successfully simulates 31 risk scenarios with an accuracy rate of 93.55%.
Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material ...
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Technological developments have resulted in a trend of cryptocurrencies that use a technology called blockchain to create and record all transactions made into a digital ledger. Along with the emergence of the trend o...
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Recently, the research on daily health monitoring using a wearable sensor has been continually evolving. In the future, when this system is actually implemented, a vast amount of data transmission will be conducted fr...
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Wireless sensors and actor networks (WSANs) have been widely used in various fields, from basic data collection to precise real-time control and monitoring, including battlefield monitoring, rescue, and exploration. T...
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The amazing capacity of Long Short-Term Memory (LSTM) networks to record complex temporal connections in sequential data has drawn a lot of attention in recent years. In the context of stock market prediction, a field...
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An information system is an important part in an organization to support business processes and to achieve its vision and mission. The information system nowadays has been one of the assets that ought to be protected ...
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