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The block cipher AES (Advanced Encryption Standard) is a cryptographic algorithm used to guarantee the confidentiality of a message. A masked implementation of AES is often used to increase resistance against SCA (Side Channel Attacks). This paper ...
Whole slide imaging is now being used across the world in pathology labs for an accurate diagnosis of biopsy specimens. However, due to the large size of these images, an automatic deep learning-based method is highly desirable for diagnosing. Herein, ...
In recent years, cloud service has been used in many field. In particular, a micro datacenter based on edge computing has been used to overcome the limitations of latency and bandwidth of cloud network architecture. Micro datacentre is small-scaled to ...
With successful applications of machine learning to various domains, there have been large demands on developing machine learning-based applications. Automated machine learning is crucial to meet the demand because there are not sufficiently many expert ...
In recent years, spiking neural networks (SNNs), a computing model inspired by the brain's ability to code and process information in the time domain with great computational power, has drawn a lot of attention from researchers for learning ...
Knowledge distillation is a strategy to build machine learning models efficiently by making use of knowledge embedded in a pretrained model. Teacher-student framework is a well-known one to use knowledge distillation, where a teacher network usually ...
Stroke is a high-risk disease causing death, permanent disability in patients, and is the leading cause of death worldwide. Stroke can be quickly examined for disease through CT, an imaging diagnostic tool. However, the diagnosis of Ischemic Stroke ...
The usage of quadcopter types of drones is now on mature and a practical stage and many major manufacturers are expanding its applications into various regions with it. Considerable characteristic of this type of flying object as its maneuverability and ...
With the recent rapid development of computing power, interest in machine learning research on large data sets is increasing significantly. The machine learning is used in a wide variety of fields, from information retrieval, data mining, and speech ...
In modern computing, log files provide a wealth of information regarding the past of a system, including the system failures and security breaches that cost companies and developers a fortune in both time and money. While this information can be used to ...
In the present era, internet of things (IoT) is prevailing very much in our daily life serving the concept of the smart applications, in which one can operate remote objects from a distant place. However, connectivity of the billions of devices has ...
Semantic classification of scientific literature using machine learning approaches is challenging due to the lack of labeled data and the length of text [1, 4]. Most of the work has been done for keyword based categorization tasks, which take care of ...
Apart from the accuracy, the size of Convolutional Neural Networks (CNN) model is another principal factor for facilitating the deployment of models on memory, power and budget constrained devices. Conventional compression techniques require human ...
This paper discusses the multi-content disentanglement issue in unsupervised image transfer model. Image transfer based on generative model such as VAE1 or GAN2 can be defined as mapping data from source domain to target domain. Existing disentanglement ...
Sentiment transfer has been explored as non-parallel transfer tasks in natural language processing. Previous works depend on a single encoder to disentangle either positive or negative style from its content and rely on a style representation to ...
The technology of deep learning has grown rapidly and been widely used in the industry. In addition to the accuracy of the deep learning (DL) models, system developers are also interested in comprehending their performance aspects to make sure that the ...
As Computer-Assisted Surgery (CAS) getting popular, more and more research has been conducted to help surgeons operate. We aim at the semantic segmentation in the endoscopy surgery scenario because semantic segmentation is the first step for a computer ...
Due to the rapid evolution of the next-generation sequencing (NGS) technology, the sequence of an individual's genome can be determined from billions of short reads at a decreasing cost, which has advanced the fields of medical research and precision ...
Neural Architecture Search (NAS) is a technique for finding suitable neural network architecture models for given applications. Previously, such search methods are usually based on reinforcement learning, with a recurrent neural network to generate ...
Accurate gender classification from fingerprint-images brings benefits to various forensic, security and authentication analysis. Those benefits help to narrow down the space for searching and speed up the process for matching for applications such as ...