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Topic Review
Federated Meta-Learning for Driver Distraction Detection
Driver distraction detection (3D) is essential in improving the efficiency and safety of transportation systems. Federated learning (FL) is emerging as a feasible solution that can train models without private and sensitive information leaving its local repository. Even though various solutions are proposed by using FL to upgrade the model learning paradigm of 3D, considering the requirements for user privacy and the phenomenon of data growth in real-world scenarios, existing methods are insufficient to address four emerging challenges, i.e., data accumulation, communication optimization, data heterogeneity, and device heterogeneity. 
  • 611
  • 27 Oct 2023
Topic Review
Keystroke Dynamics in Personal Characteristics Protection
The rapid development of information and communication technologies and the widespread use of the Internet has made it imperative to implement advanced user authentication methods based on the analysis of behavioural biometric data. In contrast to traditional authentication techniques, such as the simple use of passwords, these new methods face the challenge of authenticating users at more complex levels, even after the initial verification. This is particularly important as it helps to address risks such as the possibility of forgery and the disclosure of personal information to unauthorised individuals. Users can be categorised using keystroke dynamics, in terms of the age group they belong to and in terms of their educational level, with high accuracy rates, which is a strong indication for the creation of applications to enhance user security and facilitate their use of Internet services.
  • 610
  • 06 Nov 2023
Topic Review
UNet and Conventional DL Systems for CAD
The ability of UNet-based deep learning models as shown before is very powerful in the imaging domain and can handle image noise, structure, scale, size, resolution, and further, the variability in the shapes.
  • 609
  • 22 Dec 2023
Topic Review
CNN Models for Skin Lesions Detection
Skin cancer is a widespread disease that typically develops on the skin due to frequent exposure to sunlight. Although cancer can appear on any part of the human body, skin cancer accounts for a significant proportion of all new cancer diagnoses worldwide. There are substantial obstacles to the precise diagnosis and classification of skin lesions because of morphological variety and indistinguishable characteristics across skin malignancies. Deep learning models have been used in the field of image-based skin-lesion diagnosis and have demonstrated diagnostic efficiency on par with that of dermatologists. 
  • 609
  • 22 Feb 2024
Topic Review
Challenge of  UAV-Based Vehicle Re-Identification
Vehicle re-identification research under surveillance cameras has yielded impressive results. However, the challenge of unmanned aerial vehicle (UAV)-based vehicle re-identification (ReID) presents a high degree of flexibility, mainly due to complicated shooting angles, occlusions, low discrimination of top–down features, and significant changes in vehicle scales. 
  • 607
  • 06 Nov 2023
Topic Review
Federated Learning Models Based on DAG Blockchain
With the development of the power internet of things, the traditional centralized computing pattern has been difficult to apply to many power business scenarios, including power load forecasting, substation defect detection, and demand-side response. How to perform efficient and reliable machine learning tasks while ensuring that user data privacy is not violated has attracted the attention of the industry. Blockchain-based federated learning (FL), proposed as a new decentralized and distributed learning framework for building privacy-enhanced IoT systems, is receiving more and more attention from scholars.
  • 607
  • 22 Nov 2023
Topic Review
Commonsense Causal Reasoning
Commonsense causal reasoning is the process of understanding the causal dependency between common events or actions. Traditionally, it was framed as a selection problem. However, it cannot obtain enough candidates and needs more flexible causes (or effects) in many scenarios, such as causal-based QA problems. Thus, the ability to generate causes (or effects) is an important problem.
  • 607
  • 13 Dec 2023
Topic Review
Facial Expression Recognition Using Local Sliding Window Attention
There are problems associated with facial expression recognition (FER), such as facial occlusion and head pose variations. These two problems lead to incomplete facial information in images, making feature extraction extremely difficult. 
  • 607
  • 25 Dec 2023
Topic Review
Distributed Bayesian Inference for Large-Scale IoT Systems
The Internet of Things (IoT) has emerged as a transformative force in contemporary society, substantially impacting various facets of daily life. Nevertheless, the IoT ecosystem’s rapid expansion is accompanied by a significant increase in data generation, known as Big Data. This expansion presents a complex challenge, necessitating advanced, scalable, and efficient data processing techniques. Given the complex nature of large-scale data analysis in IoT systems, distributed Bayesian inference arises as a practical and efficient solution in this domain. Bayesian methods, which are influential in deriving informed conclusions and predictions from complex datasets, are widely recognized for their probabilistic underpinnings.
  • 607
  • 28 Dec 2023
Topic Review
Blockchain in the Peer-to-Peer Energy Trades
Advancements in rooftop solar panel technology have sparked a revolution in the electricity markets. This has given rise to a new concept of energy exchange—the ability for consumers and producers to trade localized energy. This concept has been made possible by the emergence of blockchain technology, which has gained significant traction in the energy markets. Its unique ability to facilitate peer-to-peer (P2P) energy transactions has made it a promising solution for the trilemma of scalability, security, and decentralization. 
  • 607
  • 23 Feb 2024
Topic Review
Semantically Interoperable Social Media Platforms
Competitive intelligence in social media analytics has significantly influenced behavioral finance worldwide in recent years; it is continuously emerging with a high growth rate of unpredicted variables per week. Several surveys in this large field have proved how social media involvement has made a trackless network using machine learning techniques through web applications and Android modes using interoperability.
  • 606
  • 19 Sep 2023
Topic Review
Audio–Visual Emotion Recognition
Emotion recognition can be formulated as a problem where some source produces several streams of data (features) of various modalities (e.g., audio and video), each with its own distribution, and the goal is to estimate the distributions and map them onto the source.
  • 606
  • 21 Nov 2023
Topic Review
Smart Sensing-Based Intelligent Healthcare System for Diabetes Patients
An Artificial Intelligence (AI)-enabled human-centered smart healthcare monitoring system can be useful in life saving, specifically for diabetes patients. Diabetes and heart patients need real-time and remote monitoring and recommendation-based medical assistance. Such human-centered smart healthcare systems can not only provide continuous medical assistance to diabetes patients but can also reduce overall medical expenses. In the last decade, machine learning has been successfully implemented to design more accurate and precise medical applications. 
  • 605
  • 08 Dec 2023
Topic Review
Blockchain-Based Federated Learning
Federated Learning (FL) is a distributed Deep Learning (DL) technique that creates a global model through the local training of multiple edge devices. It uses a central server for model communication and the aggregation of post-trained models. The central server orchestrates the training process by sending each participating device an initial or pre-trained model for training. To achieve the learning objective, focused updates from edge devices are sent back to the central server for aggregation. While such an architecture and information flows can support the preservation of the privacy of participating device data, the strong dependence on the central server is a significant drawback of this framework. Having a central server could potentially lead to a single point of failure. Further, a malicious server may be able to successfully reconstruct the original data, which could impact on trust, transparency, fairness, privacy, and security. Decentralizing the FL process can successfully address these issues. Integrating a decentralized protocol such as Blockchain technology into Federated Learning techniques will help to address these issues and ensure secure aggregation.
  • 603
  • 14 Nov 2023
Topic Review
Anomaly Detection in Electrocardiogram Sensor Data
Monitoring heart electrical activity is an effective way of detecting existing and developing conditions. This is usually performed as a non-invasive test using a network of up to 12 sensors (electrodes) on the chest and limbs to create an electrocardiogram (ECG). By visually observing these readings, experienced professionals can make accurate diagnoses and, if needed, request further testing. However, the training and experience needed to make accurate diagnoses are significant. 
  • 602
  • 01 Mar 2024
Topic Review
Application of Deep Learning in Cancer Diagnoses
The application of deep learning technology to realize cancer diagnosis based on medical images is one of the research hotspots in the field of artificial intelligence and computer vision. Deep learning has succeeded greatly in medical image-based cancer diagnosis. 
  • 601
  • 19 Jul 2023
Topic Review
Prediction of Cellular Network Traffic
Cellular communication systems have continued to develop in the direction of intelligence. The demand for cellular networks is increasing as they meet the public’s pursuit of a better life. Accurate prediction of cellular network traffic can help operators avoid wasting resources and improve management efficiency. Traditional prediction methods can no longer perfectly cope with the highly complex spatiotemporal relationships of the current cellular networks, and prediction methods based on deep learning are constantly growing.
  • 601
  • 14 Aug 2023
Topic Review
Few-Shot Object Detection
Few-shot object detection (FSOD) aims at designing models that can accurately detect targets of novel classes in a scarce data regime. 
  • 601
  • 16 Oct 2023
Topic Review
Drone Based RGBT Tracking with Dual-Feature Aggregation Network
In the field of UAV-based object tracking, the use of infrared mode can improve the robustness of the tracker in the scene with severe illumination changes, occlusion and expand the applicable scenarios of UAV-based object tracking tasks. Inspired by the great achievements of Transformer architecture in the field of RGB object tracking, a dual-mode object tracking network based on Transformer can be designed.
  • 601
  • 18 Jan 2024
Topic Review
Severity Identification of Parkinson’s Disease
Disease severity identification using computational intelligence-based approaches is gaining popularity nowadays. Movement disorders caused by PD may not remain the same in different patients. Thus, it is essential to develop an automated tool to evaluate a patient’s gait.
  • 599
  • 14 Apr 2023
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