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Topic Review
Deep Learning for IDSs in Time Series Data
Classification-based intrusion detection systems (IDSs) use machine learning algorithms to classify incoming data into different categories based on a set of features. Even though classification-based IDSs are effective in detecting known attacks, they can be less effective in identifying new and unknown attacks that have a small correlation with the training dataset. On the other hand, anomaly detection-based approaches use statistical models and machine learning algorithms to establish a baseline of normal behavior and identify deviations from that baseline.
  • 528
  • 29 Feb 2024
Topic Review
Authentication Methods for Mobile Device Users
With the advent of smart mobile devices, end users get used to transmitting and storing their individual privacy in them, which, however, has aroused prominent security concerns inevitably. Numerous researchers have primarily proposed to utilize motion sensors to explore implicit authentication techniques. 
  • 527
  • 14 Sep 2023
Topic Review
Recursive Decomposition–Reconstruction–Ensemble Method with Complexity Traits
The subject of oil price forecasting has obtained an incredible amount of interest from academics and policymakers in recent years due to the widespread impact that it has on various economic fields and markets. Thus, a novel method based on decomposition–reconstruction–ensemble for crude oil price forecasting is proposed. Based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique,  a recursive CEEMDAN decomposition–reconstruction–ensemble model considering the complexity traits of crude oil data was constructed. In this model, the steps of mode reconstruction, component prediction, and ensemble prediction are driven by complexity traits. For illustration and verification purposes, the West Texas Intermediate (WTI) and Brent crude oil spot prices are used as the sample data. The empirical result demonstrates that the proposed model has better prediction performance than the benchmark models.
  • 525
  • 28 Jul 2023
Topic Review
Scale-Arbitrary Super-Resolution for Satellite Images
The advancements in image super-resolution technology have led to its widespread use in remote sensing applications. The existing scale-arbitrary super-resolution methods are primarily predicated on learning either a discrete representation (DR) or a continuous representation (CR) of the image, with DR retaining the sensitivity to resolution and CR guaranteeing the generalization of the model.
  • 525
  • 23 Nov 2023
Topic Review
Multi-Task Learning, Multi-Branch Networks, and Attention Mechanisms
Diabetic Retinopathy (DR) is one of the most common microvascular complications of diabetes. Diabetic Macular Edema (DME) is a concomitant symptom of DR. As the grade of lesion of DR and DME increases, the possibility of blindness can also increase significantly. To take early interventions as soon as possible to reduce the likelihood of blindness, it is necessary to perform both DR and DME grading. 
  • 525
  • 18 Jan 2024
Topic Review
Perceptual Encryption-Based Image Communication System for Tuberculosis Diagnosis
Block-based perceptual encryption (PE) algorithms are becoming popular for multimedia data protection because of their low computational demands and format-compliancy with the JPEG standard. In conventional methods, a colored image as an input is a prerequisite to enable smaller block size for better security. However, in domains such as medical image processing, unavailability of color images makes PE methods inadequate for their secure transmission and storage. A PE method that is applicable for both color and grayscale images is proposed. The EfficientNetV2-based model is implemented for automatic tuberculosis (TB) diagnosis in chest X-ray images.
  • 524
  • 21 Sep 2022
Topic Review
Domain Shift Analyzer for Multi-Center MRI Datasets
Multi-center magnetic resonance imaging (MRI) datasets, incorporating data from multiple imaging centers or institutions, offer a unique opportunity to leverage diverse patient demographics, equipment, imaging platforms, and protocols.
  • 524
  • 24 Oct 2023
Topic Review
Network Incident Identification through Genetic Algorithm-Driven Feature Selection
The cybersecurity landscape presents daunting challenges, particularly in the face of Denial of Service (DoS) attacks such as DoS Http Unbearable Load King (HULK) attacks and DoS GoldenEye attacks. These malicious tactics are designed to disrupt critical services by overwhelming web servers with malicious requests.
  • 522
  • 30 Jan 2024
Topic Review
Explainable Artificial Intelligence in Medicine
Due to the success of artificial intelligence (AI) applications in the medical field over the past decade, concerns about the explainability of these systems have increased. The reliability requirements of black-box algorithms for making decisions affecting patients pose a challenge even beyond their accuracy. Recent advances in AI increasingly emphasize the necessity of integrating explainability into these systems. While most traditional AI methods and expert systems are inherently interpretable, the recent literature has focused primarily on explainability techniques for more complex models such as deep learning.
  • 519
  • 16 Oct 2023
Topic Review
Cross-Lingual Document Retrieval
Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information.
  • 517
  • 24 Feb 2023
Topic Review
Brain Tumor Segmentation, Deep Learning and GAN Network
Images of brain tumors may only show up in a small subset of scans, so important details may be missed. Further, because labeling is typically a labor-intensive and time-consuming task, there are typically only a small number of medical imaging datasets available for analysis. 
  • 516
  • 10 Nov 2023
Topic Review
Facial Expression Image Classification
As emotional states are diverse, simply classifying them through discrete facial expressions has its limitations. Therefore, to create a facial expression recognition system for practical applications, not only must facial expressions be classified, emotional changes must be measured as continuous values.
  • 515
  • 15 Aug 2023
Topic Review
Comprehensive Background on Tiny Machine Learning
Internet of Things (IoT) systems frequently generate vast quantities of data, posing substantial management and analysis challenges. Researchers have introduced several frameworks and architectures to address these challenges in IoT Big Data management and knowledge extraction. One such proposal is the Cognitive-Oriented IoT Big Data Framework (COIB Framework), as outlined in Mishra’s works. This framework encompasses an implementation architecture, layers for IoT Big Data, and a structure for organizing data. An alternative method involves employing a Big-Data-enhanced system, adhering to a data lake architecture. Key features of this system include a multi-threaded parallel approach for data ingestion, strategies for storing both raw and processed IoT data, a distributed cache layer, and a unified SQL-based interface for exploring IoT data. Furthermore, blockchain technologies have been investigated for their potential to maintain continuous integrity in IoT Big Data management. This involves five integrity protocols implemented across three stages of IoT operations.
  • 515
  • 01 Feb 2024
Topic Review
Deep Learning for Alzheimer’s Disease
Alzheimer’s and related diseases are significant health issues of this era. The interdisciplinary use of deep learning in this field has shown great promise and gathered considerable interest. 
  • 512
  • 25 Jun 2023
Topic Review
Machine Learning Applications in Agriculture
Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing are propelling the agricultural sector towards the transformative Agriculture 4.0 paradigm. 
  • 512
  • 08 Dec 2023
Topic Review
Integrate Artificial Intelligence into Teaching
Artificial intelligence (AI) is no longer science fiction. It is so close to our daily life that there is even existing legislation and norming like in an ISO standard. But despite these developments, AI has barely entered the consciousness of ordinary users of IT. In an academic context, the importance of AI is well recognized and there are notable efforts to integrate AI into teaching and development of teaching, for example, in curricular development or even to pass an exam. 
  • 511
  • 11 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.
  • 511
  • 15 Sep 2023
Topic Review
Weakly Supervised Crowd-Counting Models
Crowd-counting networks have become the mainstream method to deploy crowd-counting techniques on resource-constrained devices. Significant progress has been made in this field, with many outstanding lightweight models being proposed successively.  However, challenges like scare variation, global feature extraction, and fine-grained head annotation requirements still exist in relevant tasks, necessitating further improvement. In this research, the researchers propose a weakly-supervised hybrid lightweight crowd-counting network that integrates the initial layers of GhostNet as the backbone to efficiently extract local features and enrich intermediate features. The experimental results for accuracy and inference speed evaluation on some mainstream datasets validate the effective design principle of the model.
  • 506
  • 28 Feb 2024
Topic Review
Breast Cancer Diagnosis Based on Deep Mutual Learning
Breast cancer (BC) is the most common kind of cancer in women, accounting for around 30% of all new cancer diagnoses; it is also the second most fatal malignancy after lung and bronchial cancers. Centered on deep convolutional neural networks, a new BC histopathological image category blind inpainting convolutional neural network (BiCNN) model has been developed. It was developed to cope with the two-class categorization of BC on the diagnostic image.
  • 503
  • 05 Jan 2024
Topic Review
AI-Based Model for Knowledge Evaluation in Public Organizations
In the construction of knowledge bases, it is very important to evaluate the quality of the knowledge entered into them. Artificial Intelligence (AI) development has led to the research of knowledge management tools for multi-user environments, among many other AI applications. In the knowledge management field, the construction of ontologies as knowledge repositories using various sources requires a means of evaluation of all: the input ontologies and the integration process on the output ontology. The results obtained from the evaluations serve as guides to measure the quality of the repository.
  • 501
  • 01 Nov 2023
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