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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. 
  • 555
  • 25 Jun 2023
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.
  • 553
  • 21 Sep 2022
Topic Review
Tasks for Multimodal Federated Learning
Multimodal federated learning (MFL) offers many advantages, such as privacy preservation and addressing the data silo problem. However, it also faces limitations such as communication costs, data heterogeneity, and hardware disparities compared to centralized multimodal learning. Therefore, in addition to the unique challenges of modal heterogeneity, the original multimodal learning tasks become more challenging when performed within a federated learning framework.
  • 553
  • 16 Aug 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.
  • 552
  • 23 Nov 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.
  • 551
  • 30 Jan 2024
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.
  • 550
  • 28 Jul 2023
Topic Review
Soybean Monitoring and Management
The interest in deep learning in agriculture has been continuously growing since the inception of this type of technique in the early 2010s. Soybeans, being one of the most important agricultural commodities, has frequently been the target of efforts in this regard. It can be challenging to keep track of a constantly evolving state of the art.
  • 549
  • 23 Aug 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. 
  • 546
  • 08 Dec 2023
Topic Review
Higher Accuracy in YOLO Detection for Vehicle Inspection
Against the backdrop of ongoing urbanization, issues such as traffic congestion and accidents are assuming heightened prominence, necessitating urgent and practical interventions to enhance the efficiency and safety of transportation systems. A paramount challenge lies in realizing real-time vehicle monitoring, flow management, and traffic safety control within the transportation infrastructure to mitigate congestion, optimize road utilization, and curb traffic accidents.
  • 546
  • 22 Dec 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.
  • 545
  • 15 Aug 2023
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.
  • 545
  • 29 Feb 2024
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.
  • 542
  • 24 Oct 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. 
  • 541
  • 10 Nov 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.
  • 537
  • 01 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. 
  • 534
  • 14 Sep 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.
  • 532
  • 24 Feb 2023
Topic Review
Olive Leaf Disease Diagnosis
Artificial intelligence has many applications in various industries, including agriculture. It can help overcome challenges by providing efficient solutions, especially in the early stages of development. When working with tree leaves to identify the type of disease, diseases often show up through changes in leaf color. Therefore, it is crucial to improve the color brightness before using them in intelligent agricultural systems.
  • 532
  • 24 Nov 2023
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.
  • 530
  • 16 Oct 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.
  • 528
  • 28 Feb 2024
Topic Review
Digital Twins for Access Networks
As the complexity and scale of modern networks continue to grow, the need for efficient, secure management, and optimization becomes increasingly vital. Digital twin (DT) technology has emerged as a promising approach to address these challenges by providing a virtual representation of the physical network, enabling analysis, diagnosis, emulation, and control. The emergence of Software-defined network (SDN) has facilitated a holistic view of the network topology, enabling the use of Graph neural network (GNN) as a data-driven technique to solve diverse problems in future networks.
  • 523
  • 06 Dec 2023
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