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Topic Review
Eye-Tracking-Based Trail-Making Test to Detect Cognitive Impairment
The growing number of people with cognitive impairment will significantly increase healthcare demand. Screening tools are crucial for detecting cognitive impairment due to a shortage of mental health experts aiming to improve the quality of life for those living with this condition. Eye tracking is a powerful tool that can provide deeper insights into human behavior and inner cognitive processes. The proposed Eye-Tracking-Based Trail-Making Test, ETMT, is a screening tool for monitoring a person’s cognitive function.
  • 730
  • 21 Aug 2023
Topic Review
Generating Paraphrase Using Simulated Annealing for Citation Sentences
The paraphrase generator for citation sentences is used to produce several sentence alternatives to avoid plagiarism. Furthermore, the generation results need to pay attention to semantic similarity and lexical divergence standards. The generation process is guided by an objective function using a simulated annealing algorithm to maintain the properties of semantic similarity and lexical divergence. The objective function is created by combining the two factors that maintain these properties.
  • 729
  • 01 Dec 2023
Topic Review
Integration of Deep Learning into the IoT
The internet of things (IoT) has emerged as a pivotal technological paradigm facilitating interconnected and intelligent devices across multifarious domains. The proliferation of IoT devices has resulted in an unprecedented surge of data, presenting formidable challenges concerning efficient processing, meaningful analysis, and informed decision making. Deep-learning (DL) methodologies, notably convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep-belief networks (DBNs), have demonstrated significant efficacy in mitigating these challenges by furnishing robust tools for learning and extraction of insights from vast and diverse IoT-generated data.
  • 729
  • 19 Dec 2023
Topic Review
Segmentation and Path Planning of Unmanned Ariel Vehicle
Unmanned aerial vehicles (UAVs), sometimes known as “drones”, are unmanned aircraft that can be flown without a pilot on board. Aircraft, ground control stations, and communications systems all fall under the umbrella term unmanned aircraft systems (UAS), which describes the infrastructure necessary for sophisticated drone operations. An autonomous drone is a UAV that can fly missions independently of a human pilot. It can take off, execute its task, and return to base without human assistance. Rather than relying on a human pilot, communications management software handles mission planning and flight control for autonomous drones.
  • 729
  • 15 Dec 2023
Biography
Obinna Johnphill
Obinna Johnphill is a remarkable individual, a married man, and a devoted father of two. His journey in computer science has been one of dedication and continuous pursuit of knowledge. He laid the foundation for his academic career by earning a Bachelor of Science (Hons) in Software Development in 2014 from the University of Wolverhampton. Building on his passion for computer science, he further
  • 728
  • 26 Jul 2023
Topic Review
Zero-Shot Semantic Segmentation with No Supervision Leakage
Zero-shot semantic segmentation (ZS3), the process of classifying unseen classes without explicit training samples, poses a significant challenge. Despite notable progress made by pre-trained vision-language models, they have a problem of “supervision leakage” in the unseen classes due to their large-scale pre-trained data.
  • 728
  • 29 Aug 2023
Topic Review
Convolutional Neural Network-Based Layer-Adaptive Ground Control Points Extraction
Ground Control Points (GCPs) are of great significance for applications involving the registration and fusion of heterologous remote sensing images (RSIs). However, utilizing low-level information rather than deep features, traditional methods based on intensity and local image features turn out to be unsuitable for heterologous RSIs because of the large nonlinear radiation difference (NRD), inconsistent resolutions, and geometric distortions. Additionally, the limitations of current heterologous datasets and existing deep-learning-based methods make it difficult to obtain enough precision GCPs from different kinds of heterologous RSIs, especially for thermal infrared (TIR) images that present low spatial resolution and poor contrast.
  • 726
  • 02 Jun 2023
Topic Review
DeepSeek
DeepSeek Artificial Intelligence Co., Ltd. (referred to as "DeepSeek" or "深度求索"), founded in 2023, is a Chinese company dedicated to making AGI (Artificial General Intelligence) a reality. Focused on advancing AI technologies, DeepSeek aims to develop systems with human-like adaptability and problem-solving capabilities, contributing to innovation across industries and shaping the future of intelligent systems.
  • 726
  • 06 Feb 2025
Topic Review
Multi-Label Fundus Image Classification
Fundus images are used by ophthalmologists and computer-aided diagnostics to detect fundus disease such as diabetic retinopathy, glaucoma, age-related macular degeneration, cataracts, hypertension, and myopia.
  • 725
  • 30 Jun 2022
Topic Review
Early Detection of Intrauterine Fetal Demise
Intrauterine fetal demise in women during pregnancy is a major contributing factor in prenatal mortality and is a major global issue in developing and underdeveloped countries. When an unborn fetus passes away in the womb during the 20th week of pregnancy or later, early detection of the fetus can help reduce the chances of intrauterine fetal demise.
  • 725
  • 25 May 2023
Topic Review
Multimodal Biometric Identification System
In the past two decades, many physical and behavioral biometric modalities have been under extensive research, such as fingerprints, palm prints, palms/Finger Textures, faces, irises, voice, gait and signature. All these modalities are vulnerable to presentation spoof attacks; hence, the level of provided security is compromised. Fingerprint- and palm-print-based biometric systems may be deceived by using gelatin or clay-made artificial fingerprint surfaces or images. Biometric systems using faces as a biometric modality may be attacked by using photographs, 3-D face models and recorded short clips. Iris-based biometric systems may encounter spoof attacks by employing iris images taken from enrolled users. Voice- and gait-based biometric systems may be attacked by feeding prerecorded audio and video to the recognition system, respectively. 
  • 725
  • 21 Dec 2023
Topic Review
Fake News Detection on Social Media
The spread of fake news on social media continues to be one of the main challenges facing internet users, prohibiting them from discerning authentic from fabricated pieces of information. Detecting fake news is a problem tackled through different approaches that can be categorized mainly into a content-based approach and a social-based approach. In the content-based approach, the textual features are the main features, whereas in the social-based approach other features, including users’ engagements, users’ profile features, and network propagation features, are considered.
  • 725
  • 27 Dec 2023
Topic Review
Multi-Method Diagnosis of CT Images
Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images contain huge amounts of information, requiring a lot of experience and taking a long time for proper analysis and diagnosis. Thus, artificial intelligence techniques provide an automatic mechanism for evaluating CT images to make a diagnosis with high accuracy and help radiologists make their diagnostic decisions.
  • 724
  • 30 Aug 2022
Topic Review
Federated Learning Algorithms in Healthcare
Federated Learning (FL), an emerging distributed collaborative artificial intelligence (AI) paradigm, is particularly suitable for smart healthcare by coordinating the training of numerous clients, that is, in healthcare institutes, without the exchange of private data.
  • 723
  • 26 Dec 2022
Topic Review
The Rise of Adversarial Machine Learning
Internet of Things (IoT) technologies serve as a backbone of cutting-edge intelligent systems. Machine Learning (ML) paradigms have been adopted within IoT environments to exploit their capabilities to mine complex patterns. Despite the reported promising results, ML-based solutions exhibit several security vulnerabilities and threats. Specifically, Adversarial Machine Learning (AML) attacks can drastically impact the performance of ML models. It also represents a promising research field that typically promotes novel techniques to generate and/or defend against Adversarial Examples (AE) attacks.
  • 721
  • 29 May 2023
Topic Review
Anomaly Detection Algorithms for LAN Failure Prediction
Predicting Local Area Network (LAN) equipment failure is of utmost importance to ensure the uninterrupted operation of modern communication networks. The utilization of machine learning algorithms, specifically decision trees and support vector machines (SVMs), for predicting LAN failures represents a groundbreaking approach in network management.
  • 721
  • 13 Oct 2023
Topic Review
Deep Learning in Arabic Tweets Fake News Detection
Fake news has been around for a long time, but the rise of social networking applications has rapidly increased the growth of fake news among individuals. Fake news negatively impacts various aspects of life (economical, social, and political). Identifying fake news manually on these open platforms would be challenging as they allow anyone to build networks and publish the news in real time. Therefore, creating an automatic system for recognizing news credibility on social networks relying on artificial intelligence techniques, including machine learning and deep learning, has attracted the attention of researchers. Using deep learning methods has shown promising results in recognizing fake news written in English. 
  • 719
  • 14 Aug 2023
Topic Review
Solar Energy Generation Prediction
Energy, or more specifically electricity, is one of the most significant pillars of society. Solar Photovoltaic energy has emerged as the most flourishing source of power generation. Not only is it a clean and renewable energy, but it is also economically accessible with minimal maintenance. Nevertheless, they have the disadvantage of high dependence on climatic factors, significant variability and high cost of energy storage. Hence, forecasting the generation of Photovoltaic (PV) installations for a given period of time can help to make optimal use of resources, allowing for reduced emissions, lower costs, safe operation and better integration into the grid.
  • 717
  • 30 Nov 2023
Topic Review
Different AI-Based Algorithms for COVID-19 Vaccine Development
Millions of people have died because of the COVID-19 epidemic, and economies have been severely damaged. The creation of a secure and reliable vaccination is essential to stopping the virus’s spread and preserving human life. Artificial intelligence (AI) has shown great promise as a tool for streamlining the process and improving vaccination efficacy in the field of vaccine development. Artificial intelligence (AI) is the application of computer algorithms to tasks that normally require human intelligence, such as pattern recognition, learning, and decision making. AI can be used in vaccine development to evaluate large datasets, identify potential vaccine targets, and forecast the efficacy of vaccine candidates.
  • 715
  • 09 Jan 2024
Topic Review
Impacts of Surface Microchannels on Porous Fibrous Media
The microchannel increases the permeability of flow both in the directions parallel and vertical to the microchannel direction. The microchannel plays as the highway for the pass of reactants while the rest of the smaller pore size provides higher resistance for better catalyst support, and the propagation path in the network with microchannels is more even and predictable. 
  • 713
  • 21 Dec 2021
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