RFID technology offers an affordable and user-friendly solution for contactless identification of objects and individuals. However, the widespread adoption of RFID systems raises concerns regarding security and privac...
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The usage of online entertainment has increased dramatically after some time with the enhancement of the Internet and has turned into the most compelling systems administration stage in this century. Notwithstanding, ...
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This article is devoted to the research and development of innovative two-factor authentication (2FA) methods using neural networks. 2FA plays a key role in ensuring the security of data and accounts in the modern dig...
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The article presents a new approach in the development of software for bipedal humanoid robot controllers, based on the construction and application of graphic domain-specific languages (DSLs). The notations used to d...
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Balancing the consistency of style and the integrity of content is the main challenge in arbitrary style transfer domain. Currently, local style details can be effectively captured by attention mechanism but easily pr...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
Balancing the consistency of style and the integrity of content is the main challenge in arbitrary style transfer domain. Currently, local style details can be effectively captured by attention mechanism but easily produce distorted style patterns and inconsistent content structure. In this paper, we propose a Content Affinity Preserving Arbitrary Style Transfer (CAPAST) framework to ensure style features can be stably integrated into the content structure. Considering the local feature learning ability of CNN and the global feature representation advantage of transformer, a dual encoder is proposed to capture local and global features of images with the combination between transformer and CNN. In addition, a channel and spatially aligned attention (CSAA) is introduced to generate high-quality results by stably fusing style features and content features. In experiments, we demonstrated the superior performance of our method in preventing content structure distortion and maintaining consistency between style and content. Codes are available at https://***/miaopashi-zxy/CAPAST.
As long as a computer system is connected to the Internet, it is susceptible to attack as a victim. In computer networks, it becomes important to manage the network based on parameters such as network size and network...
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ISBN:
(数字)9798350394986
ISBN:
(纸本)9798350394993
As long as a computer system is connected to the Internet, it is susceptible to attack as a victim. In computer networks, it becomes important to manage the network based on parameters such as network size and network data. Firewalls are devices that help network administrators in this case to establish security in the network, and can be based on the rules that the firewall is based on. It is configured to control incoming and outgoing network traffic. Firewalls can be considered the most vital components of the network in establishing security. Firat University introduced a dataset containing firewall logs with multiple classes for firewall decisions. This study uses data mining techniques to improve the validation performance of classification using various machine learning algorithms like neural networks, deep learning, and kNN. The experimental results show more than 10% improvement according to precision and recall rates among various folding scenarios used in related works with minor improvement in accuracy, too. The decision tree algorithm is fast and explainable versus other algorithms.
The Disease Prediction System revolutionizes healthcare with advanced machine learning techniques for early detection of skin diseases, notably focusing on skin cancer. Through image processing and Transfer Learning, ...
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ISBN:
(数字)9798350394634
ISBN:
(纸本)9798350394641
The Disease Prediction System revolutionizes healthcare with advanced machine learning techniques for early detection of skin diseases, notably focusing on skin cancer. Through image processing and Transfer Learning, it excels in identifying potential malignancies, enabling timely interventions. Its capabilities extend to benign tumors and growth disorders, utilizing the ResNet50 Model for precise identification. Additionally, it predicts skin reactions associated with various dermatological conditions, such as Urticaria Hives and Warts, leveraging the efficientnetB0 Model. Integration of the VGG16 Model enhances diagnostic accuracy for inflammatory skin conditions. This holistic approach prioritizes patient-centric care, leveraging diverse datasets and intricate pattern recognition in medical images. The system’s proactive nature embodies personalized solutions for early detection, timely intervention, and improved patient outcomes. Its versatility and accuracy underscore itstransformative potential in healthcare delivery. By harnessing diverse datasets and recognizing intricate patterns within medical images, it heralds a new era of personalized healthcare solutions. In essence, the Disease Prediction System exemplifies the transformative potential of machine learning in healthcare, ensuring the highest standards of diagnostic accuracy and efficacy, while prioritizing patient well-being and quality oflife.
We study the optimal scheduling of graph states in measurement-based quantum computation, establishing an equivalence between measurement schedules and path decompositions of graphs. We define the spatial cost of a me...
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Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse,causing air to enter the pleural cavity,the area close to the lungs and chest *** most persistent disease,as well as one that necessitat...
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Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse,causing air to enter the pleural cavity,the area close to the lungs and chest *** most persistent disease,as well as one that necessitates particular patient care and the privacy of their health *** radiologists find it challenging to diagnose pneumothorax due to the variations in *** learning-based techniques are commonly employed to solve image categorization and segmentation ***,it is challenging to employ it in the medical field due to privacy issues and a lack of *** address this issue,a federated learning framework based on an Xception neural network model is proposed in this *** pneumothorax medical image dataset is obtained from the Kaggle *** preprocessing is performed on the used dataset to convert unstructured data into structured information to improve the model’s ***-max normalization technique is used to normalize the data,and the features are extracted from chest Xray *** dataset converts into two windows to make two clients for local model *** neural network model is trained on the dataset individually and aggregates model updates from two clients on the server *** decrease the over-fitting effect,every client analyses the results three *** 1 performed better in round 2 with a 79.0%accuracy,and client 2 performed better in round 2 with a 77.0%*** experimental result shows the effectiveness of the federated learning-based technique on a deep neural network,reaching a 79.28%accuracy while also providing privacy to the patient’s data.
Security and privacy are the leading solicitude in cloud computing since users have restricted privilege on the data maintained by distinct service providers at remote locations. The situation becomes more strenuous w...
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