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Topic Review
Quantization Methods of  Defense against Membership Inference Attacks
Machine learning deployment on edge devices has faced challenges such as computational costs and privacy issues. Membership inference attack (MIA) refers to the attack where the adversary aims to infer whether a data sample belongs to the training set. In other words, user data privacy might be compromised by MIA from a well-trained model. Therefore, it is vital to have defense mechanisms in place to protect training data, especially in privacy-sensitive applications such as healthcare. 
  • 220
  • 19 Sep 2023
Topic Review
Malicious Social Network Messages
The primary methods of communication in the modern world are social networks, which are rife with harmful messages that can injure both psychologically and financially. Most websites do not offer services that automatically delete or send malicious communications back to the sender for correction, or notify the sender of inaccuracies in the content of the messages. The deployment of such systems could make use of techniques for identifying and categorizing harmful messages.
  • 354
  • 19 Sep 2023
Topic Review
Spiking Neural Networks and Neuromorphic Modeling
Use of Spiking Neural Networks (SNNs) that can capture a model of organisms’ nervous systems, may be simply justified by their unparalleled energy/computational efficiency.
  • 181
  • 19 Sep 2023
Topic Review
Text Generation Models and Imbalanced Sentiment Analysis
The significance of sentiment analysis has extended across a wide range of fields, finding extensive use in various applications. As digital communication continues to expand, the ability of sentiment analysis to interpret complex human emotions and opinions becomes increasingly important, proving invaluable in fields ranging from social sciences to customer service and beyond. In this era of increasing digitization, leveraging the power of data through sentiment analysis offers unique insights, making significant contributions to sectors such as those previously summarized in various studies, namely, healthcare, social policy, e-commerce, and digital humanities.
  • 228
  • 18 Sep 2023
Topic Review
Skull Stripping Methods
Skull stripping removes non-brain tissues from magnetic resonance (MR) images, but it is hard because of brain variability, noise, artifacts, and pathologies. The existing methods are slower and limited to a single orientation, mostly axial. Researchers' proposed and experimented method uses the modern and robust architecture of deep learning neural networks, viz., Mask–region convolutional neural network (RCNN) to learn, detect, segment, and to apply the mask on brain features and patterns from many thousands of brain MR images.
  • 236
  • 18 Sep 2023
Topic Review
IoT/IIoT and Edge/Fog Computing
The Internet of Things (IoT) can be defined as a paradigm that utilizes intelligent devices that can communicate through the internet. The Industrial Internet of Things (IIoT) paradigm is a key research area derived from the Internet of Things (IoT). The emergence of IIoT has enabled a revolution in manufacturing and production, through the employment of various embedded sensing devices connected by an IoT network, along with a collection of enabling technologies, such as artificial intelligence (AI) and edge/fog computing. Edge computing is an enabling paradigm that exclusively processes data on the network’s edge. Fog computing is another emerging technology that enables edge devices (i.e., end devices and edge platforms) to perform additional computations, handle data, and allocate network resources.
  • 204
  • 15 Sep 2023
Topic Review
Lower Limb Disorder Identification
A novel approach for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements.
  • 180
  • 15 Sep 2023
Topic Review
Cross-Modal Dynamic Attention Neural Architecture
Detecting anomalies in data streams from smart communication environments is a challenging problem that can benefit from novel learning techniques. The Attention Mechanism is a very promising architecture for addressing this problem. It allows the model to focus on specific parts of the input data when processing it, improving its ability to understand the meaning of specific parts in context and make more accurate predictions.
  • 172
  • 15 Sep 2023
Topic Review
Optimal Design of Neural Networks Based on FPGA
Deep learning based on neural network has been widely used in image recognition, speech recognition, natural language processing, automatic driving and other fields, and has made breakthrough progress. FPGA stands out in the field of accelerated deep learning with its flexible architecture and logical unit, high energy efficiency ratio, strong compatibility, low delay and other advantages.
  • 551
  • 15 Sep 2023
Topic Review
Anterior and Inferior Myocardial Infarctions Using UWB Radar
Despite significant improvement in prognosis, myocardial infarction (MI) remains a major cause of morbidity and mortality around the globe. MI is a life-threatening cardiovascular condition that requires prompt diagnosis and appropriate treatment. The combination of ultra-wideband (UWB) radar and machine learning (ML) approaches has shown significant potential to improve the diagnosis of various medical conditions. 
  • 257
  • 15 Sep 2023
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