Cardiovascular health is becoming more common over the world. Electrocardiography (ECG) is a test that utilizes an electrical signal in the heart to diagnose and monitor cardiac problems. Utilizing the myDAQ data acqu...
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The article proposes a qualitative identification scheme of fluorescent immunoassay strips based on residual networks to address problems such as poor strip positioning accuracy and inadequate strip size specification...
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As the network security threats caused by the internet of Things (IoT) continue to increase, the attack surface continues to expand and the network heterogeneity increases, and the use of virtualization technology and...
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Joint photographic experts group (JPEG) is a widely used image compression format due to its high compression ratio and relatively good image quality. Embedding data into JPEG images is useful for many applications, s...
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With the development of technology and the increase in the need to use the internet and the transmission of personal data and save it on the cloud and personal computers and with the increase in security risks represe...
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In this paper, we propose a federated-distillation-based distributed semantic communication system for image classification tasks, called FedDistillSC, which considers multiple transmitters with varying channel condit...
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The convolutional neural network(CNN)-based method for image super-resolution(SR) reconstruction has been becoming an important part in the fields of image processing such as security monitoring, object tracking. Howe...
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With the rapid advancement of Mobile internet (MI) and wireless networks, mobile devices have become very essential tools for people's daily tasks as they can provide a wide range of services including video confe...
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Datasets of maritime objects are very important for training applications related to activity monitoring in locations around ports and shores. This paper introduces a maritime dataset for object detection, named as th...
Datasets of maritime objects are very important for training applications related to activity monitoring in locations around ports and shores. This paper introduces a maritime dataset for object detection, named as the shore livecam dataset. The dataset is a collection of high definition (HD), full high definition (FHD), and ultra high definition (UHD) images captured from live video feeds recorded across various port based areas of Germany. These images contain multiple instances of objects which are primarily classified into three different classes and annotated accordingly. The widely varying object sizes contribute to the uniqueness of this dataset whose content is thoroughly analysed and described. Finally, a selection of deep learning models is used on this dataset for evaluation. The dataset is available at https://***/HSU-ANT/shore_livecams/
Our information is constantly under threat when transmitted through public networks. So, research to keep information secret has been carried out. Mainly, steganography, which consists of hiding data in digital media,...
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