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Topic Review
Home-Based Devices for Detecting Obstructive Sleep Apnea
Obstructive Sleep Apnea (OSA) is a respiratory disorder characterized by frequent breathing pauses during sleep. The apnea–hypopnea index is a measure used to assess the severity of sleep apnea and the hourly rate of respiratory events. Despite numerous commercial devices available for apnea diagnosis and early detection, accessibility remains challenging for the general population, leading to lengthy wait times in sleep clinics. Consequently, research on monitoring and predicting OSA has surged. 
  • 773
  • 20 Feb 2024
Topic Review
Contextual Information Enhancement Network for Crack Segmentation Methods
Convolutional neural-network-based crack segmentation methods have performed excellently. However, existing crack segmentation methods still suffer from background noise interference, such as dirt patches and pitting, as well as the imprecise segmentation of fine-grained spatial structures. 
  • 772
  • 24 Nov 2022
Topic Review
Text Classification Technique
One of the effective solutions in Arabic text classification is to find the suitable feature selection method with an optimal number of features alongside the classifier. Although several text classification methods have been proposed for the Arabic language using different techniques, such as feature selection methods, an ensemble of classifiers, and discriminative features, choosing the optimal method becomes an NP-hard problem considering the huge search space. 
  • 770
  • 02 Mar 2023
Topic Review
Machine Learning-Based Approaches to IoT Localization
The widespread use of the Internet and the exponential growth in small hardware diversity enable the development of Internet of things (IoT)-based localization systems. Because of their high prediction accuracy, machine learning methods are being used to solve localization problems.
  • 769
  • 20 Apr 2023
Topic Review
Modern Greek on Social Web
Mining social web text has been at the heart of the Natural Language Processing and Data Mining research community in the last 15 years. Though most of the reported work is on widely spoken languages, such as English, the significance of approaches that deal with less commonly spoken languages, such as Greek, is evident for reasons of preserving and documenting minority languages, cultural and ethnic diversity, and identifying intercultural similarities and differences. 
  • 768
  • 01 Jun 2021
Topic Review
Deep-Learning-Powered Zero-Watermarking Scheme for Images
In order to safeguard image copyrights, zero-watermarking technology extracts robust features and generates watermarks without altering the original image. Traditional zero-watermarking methods rely on handcrafted feature descriptors to enhance their performance.
  • 768
  • 24 Jan 2024
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.
  • 766
  • 18 Sep 2023
Topic Review
Rumor Detection in Social Media
The widespread dissemination of rumors (fake information) on online social media has had a detrimental impact on public opinion and the social environment. This necessitates the urgent need for efficient rumor detection methods. 
  • 765
  • 24 Aug 2023
Topic Review
Autism with Optimized Machine Learning Models
Early diagnosis of autism is extremely beneficial for patients. Traditional diagnosis approaches have been unable to diagnose autism in a fast and accurate way; rather, there are multiple factors that can be related to identifying the autism disorder. The gene expression (GE) of individuals may be one of these factors, in addition to personal and behavioral characteristics (PBC). Machine learning (ML) based on PBC and GE data analytics emphasizes the need to develop accurate prediction models. The quality of prediction relies on the accuracy of the ML model. To improve the accuracy of prediction, optimized feature selection algorithms are applied to solve the high dimensionality problem of the datasets used. Comparing different optimized feature selection methods using bio-inspired algorithms over different types of data can allow for the most accurate model to be identified. 
  • 762
  • 05 May 2022
Topic Review
Deep Reinforcement Learning and Games
Deep learning (DL) algorithms were established in 2006 and have been extensively utilized by many researchers and industries in subsequent years. Ever since the impressive breakthrough on the ImageNet classification challenge in 2012, the successes of supervised deep learning have continued to pile up. Many researchers have started utilizing this new and capable family of algorithms to solve a wide range of new tasks, including ways to learn intelligent behaviors in reward–driven complex dynamic problems successfully. The agent––environment interaction expressed through observation, action, and reward channels is the necessary and capable condition of characterizing a problem as an object of reinforcement learning (RL). Learning environments can be characterized as Markov decision problems, as they satisfy the Markov property, allowing RL algorithms to be applied. From this family of environments, games could not be absent. In a game–based environment, inputs (the game world), actions (game controls), and the evaluation criteria (game score) are usually known and simulated. With the rise of DL and extended computational capability, classic RL algorithms from the 1990s could now solve exponentially more complex tasks such as games over time, traversing through huge decision spaces.
  • 762
  • 22 Feb 2023
Topic Review
Weakly Supervised and Unsupervised Methods in Plant Segmentation
Plant segmentation is a challenging computer vision task due to plant images complexity. We need to distinguish plant parts rather than the whole plant. The major complication of multi-part segmentation is the absence of well-annotated datasets. It is very time-consuming and expensive to annotate datasets manually on the object parts level.
  • 762
  • 04 Aug 2023
Topic Review
Epileptic Seizure Prediction Approaches
Electroencephalography (EEG) signals are the primary source for discriminating the preictal from the interictal stage, enabling early warnings before the seizure onset. Epileptic seizure prediction systems face significant challenges due to data scarcity, diversity, and privacy. 
  • 761
  • 11 Aug 2023
Topic Review
Adaptive Local Cross-Channel Interaction
Adding an attention module to the deep convolution semantic segmentation network has significantly enhanced the network performance. However, the existing channel attention module focusing on the channel dimension neglects the spatial relationship, causing location noise to transmit to the decoder.
  • 761
  • 24 Nov 2023
Topic Review
Development of AI in Surgery after SARS-CoV-2 Pandemic
SARS-CoV-2 has significantly transformed the healthcare environment, and it has triggered the development of electronic health and artificial intelligence mechanisms, for instance. 
  • 759
  • 04 Nov 2021
Topic Review
Intelligent Deep Learning in IoT Smart Home Networks
The Internet of Things (IoT) is the interconnection of sensors, machines, objects, or other computing devices over the internet to communicate with the least human interference. Specific types of sensors are involved in obtaining information from physical entities, and after analysis, it is stored in local storage, which is then sent to cloud storage, where appropriate action is taken according to the information.
  • 759
  • 03 Jan 2023
Topic Review
Generative Adversarial Networks for Computer Vision Tasks
Computer vision tasks have gained a lot of popularity, accompanied by the development of numerous powerful architectures consistently delivering outstanding results when applied to well-annotated datasets. However, acquiring a high-quality dataset remains a challenge, particularly in sensitive domains like medical imaging, where expense and ethical concerns represent a challenge. Generative adversarial networks (GANs) offer a possible solution to artificially expand datasets, providing a basic resource for applications requiring large and diverse data. 
  • 759
  • 23 Feb 2024
Topic Review
Sensor-Based Gesture Recognition and Algorithm
Traditional vision-based gesture recognition technology has matured, it has significant limitations in underwater environments. The cost of underwater cameras is high, the underwater shooting environment is complex, and it is very easy to be disturbed by water flow, water bubbles, etc., which hinder the line of sight and make shooting difficult. Sensor-based gesture recognition technology has become popular for underwater gesture recognition because of its lower cost and higher stability (not easily affected by the underwater environment).
  • 756
  • 12 Nov 2023
Topic Review
Transformer-Based Visual Object Tracking
With the rise of general models, transformers have been adopted in visual object tracking algorithms as feature fusion networks. In these trackers, self-attention is used for global feature enhancement. Cross-attention is applied to fuse the features of the template and the search regions to capture the global information of the object. However, studies have found that the feature information fused by cross-attention does not pay enough attention to the object region. In order to enhance cross-attention for the object region, an enhanced cross-attention (ECA) module is proposed for global feature enhancement.
  • 753
  • 08 Dec 2023
Topic Review
Securing ATM Payment Transactions
Credit/debit cards are a ubiquitous form of payment at present. They offer a number of advantages over cash, including convenience, security, and fraud protection. In contrast, the inherent vulnerabilities of credit/debit cards and transaction methods have led many payment institutions to focus on strengthening the security of these electronic payment methods. Also, the increasing number of electronic payment transactions around the world have led to a corresponding increase in the amount of money lost due to fraud and cybercrime. This loss of money has a significant impact on businesses and consumers, and it necessitates the development of rigid and robust security designs for securing underlying electronic transaction methods.
  • 753
  • 14 Nov 2023
Topic Review
Low-Light Object Tracking in UAV Videos
Unmanned aerial vehicles (UAVs) visual object tracking under low-light conditions serves as a crucial component for applications, such as night surveillance, indoor searches, night combat, and all-weather tracking. However, the majority of the existing tracking algorithms are designed for optimal lighting conditions. In low-light environments, images captured by UAV typically exhibit reduced contrast, brightness, and a signal-to-noise ratio, which hampers the extraction of target features. Moreover, the target’s appearance in low-light UAV video sequences often changes rapidly, rendering traditional fixed template tracking mechanisms inadequate, and resulting in poor tracker accuracy and robustness. 
  • 751
  • 21 Aug 2023
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