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Topic Review
Cultural Heritage Buildings in Athens
Architectural structures, the basic elements of the urban web, are an aggregation of buildings that have been built at different times, with different materials, and in different styles. Through research, they can be divided into groups that present common morphological attributes and refer to different historical periods with particular social, economic, and cultural characteristics.
  • 578
  • 16 Jan 2024
Topic Review
Sequential Tracking Models, Physics-Based Models and Hybrid Models
Spatio-temporal, geo-referenced datasets are rapidly expanding and will continue to do so in the near future due to technological advancements as well as social and commercial factors. The introduction of the automatic identification system (AIS), which allows neighboring ships to communicate frequently with their location and navigation status via a radio signal, has enabled researchers to get their hands on datasets rich in spatio-temporal information. AIS data are collected from satellites and ground stations located all over the world. AIS data facilitates the mapping and characterization of maritime human and vessel activities, thus allowing for the real-time geo-tracking and identification of vessels equipped with AIS. Hence, in addition to its initial application in collision avoidance, AIS is now also a massive data source of unparalleled quality for diverse tracking tasks. The AIS dataset contains the location and motion features of the vessels. Each data point or row in the AIS data file is represented by a time-sequenced node that contains the vessel’s coordinates, speed, and traveling direction. Each node also has an associated time stamp indicating the data collection time. AIS dataset is suitable for  the track association problem solving approach for its spatio-temporal characteristics.
  • 577
  • 07 Aug 2023
Topic Review
Point Cloud Semantic Segmentation
For autonomous vehicles driving in off-road environments, it is crucial to have a sensitive environmental perception ability. However, semantic segmentation in complex scenes remains a challenging task. Most current methods for off-road environments often have the problems of single scene and low accuracy. 
  • 577
  • 20 Oct 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.
  • 577
  • 13 Dec 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. 
  • 576
  • 16 Oct 2023
Topic Review
Models for Enhancing Autonomous Driving Accuracy
Higher-level autonomous driving necessitates the best possible execution of important moves under all conditions. Most of the accidents caused by the AVs launched by leading automobile manufacturers are due to inadequate decision-making, which is a result of their poor perceivance of environmental information. In today’s technology-bound scenarios, versatile sensors are used by AVs to collect environmental information. Due to various technical and natural calamities, the environmental information acquired by the sensors may not be complete and clear, due to which the AVs may misinterpret the information in a different context, leading to inadequate decision-making, which may then lead to fatal accidents. To overcome this drawback, effective preprocessing of raw sensory data is a mandatory task. Pre-processing the sensory data involves two vital tasks, namely data cleaning and data fusion. Since the raw sensory data are complex and exhibit multimodal characteristics, more emphasis is given to data preprocessing. 
  • 576
  • 12 Oct 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. 
  • 576
  • 25 Dec 2023
Topic Review
Insulator Defect Detection
Insulators, as important components of high-voltage transmission lines, serve the functions of electrical separation and support for conductors. Due to their long-term outdoor exposure to sunlight, rain, climate changes, and chemical corrosion, insulators often suffer from self-exploding defects, causing the disconnection of insulator strings and interfering with their performance, thus affecting the safety and stability of power systems. Insulator detection methods are generally divided into two types. The first is manual inspection, where workers directly observe insulators to identify defective parts. However, this method is time-consuming and not safe. The second is intelligent inspection, which can effectively locate defective parts by carrying edge detection equipment on drones for regular inspection of insulators. This is also the current mainstream inspection method.
  • 576
  • 26 Jan 2024
Topic Review
DiabeticSense
Diabetes mellitus is a widespread chronic metabolic disorder that requires regular blood glucose level surveillance. Current invasive techniques, such as finger-prick tests, often result in discomfort, leading to infrequent monitoring and potential health complications. Researchers was to design a novel, portable, non-invasive system for diabetes detection using breath samples, named DiabeticSense, an affordable digital health device for early detection, to encourage immediate intervention. The device employed electrochemical sensors to assess volatile organic compounds in breath samples, whose concentrations differed between diabetic and non-diabetic individuals. The system merged vital signs with sensor voltages obtained by processing breath sample data to predict diabetic conditions.
  • 575
  • 29 Dec 2023
Topic Review
Time Optimization of Drones Using an Augmented Path
With the pandemic gripping the entire humanity and with uncertainty hovering like a black cloud over all our future sustainability and growth, it became almost apparent that though the development and advancement are at their peak, we are still not ready for the worst. New and better solutions need to be applied so that we will be capable of fighting these conditions. One such prospect is delivery, where everything has to be changed, and each parcel, which was passed people to people, department to department, has to be made contactless throughout with as little error as possible. Thus, the prospect of drone delivery and its importance came around with optimization of the existing system for making it useful in the prospects of delivery of important items like medicines, vaccines, etc. These modular AI-guided drones are faster, efficient, less expensive, and less power-consuming than the actual delivery. 
  • 574
  • 10 Dec 2021
Topic Review
Negotiation Protocol with Pre-Domain Narrowing
Consensus building among agents is crucial in multi-agent system because each agent acts independently according to its utility function, and conflict among agents can occur. Therefore, automated negotiation is an essential technology for efficiently resolving conflicts and forming consensuses while also keeping agents' privacy. As the domain to be negotiated is large, the computational cost of reaching a consensus increases and the agreement rate decreases. Some negotiation protocols have been proposed wherein a mediator collects the utility information of each agent and creates multiple alternatives of agreements to handle large-scale multi-issue negotiations. However, in such protocols, a limitation is placed on agents' privacy because all agents have to disclose their private information by following the mediator and predecided negotiation rules.
  • 574
  • 05 Jun 2023
Topic Review
Expression-Guided Deep Joint Learning for Facial Expression Recognition
As one of the most fundamental tasks in face analysis, facial expression recognition (FER) plays an important role in understanding emotional states and intentions. FER also provides support in a variety of important societal applications, including intelligent security, fatigue surveillance, medical treatment, and consumer acceptance prediction. 
  • 574
  • 22 Sep 2023
Topic Review
Deep Learning for Alzheimer’s Disease Detection
Deep learning has become a prominent approach in Alzheimer’s disease (AD) detection using medical image data, incorporating modalities like positron emission tomography (PET) and magnetic resonance imaging (MRI). These advances in deep learning and multimodal imaging have improved AD detection accuracy and effectiveness, leveraging convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative modelling techniques. 
  • 574
  • 05 Mar 2024
Topic Review
Anterior and Inferior Myocardial Infarctions Using UWB Radar
Despite significant improvement in prognosis, myocardial infarction (MI) remains a major cause of morbidity and mortality around the globe. MI is a life-threatening cardiovascular condition that requires prompt diagnosis and appropriate treatment. The combination of ultra-wideband (UWB) radar and machine learning (ML) approaches has shown significant potential to improve the diagnosis of various medical conditions. 
  • 573
  • 15 Sep 2023
Topic Review
GAN-Based Tabular Data Generator for Constructing Synopsis
In data-driven systems, data exploration is imperative for making real-time decisions. However, big data are stored in massive databases that are difficult to retrieve. Approximate Query Processing (AQP) is a technique for providing approximate answers to aggregate queries based on a summary of the data (synopsis) that closely replicates the behavior of the actual data. The use of Generative Adversarial Networks (GANs) for generating tabular data has emerged as a pivotal method in AQP for constructing accurate synopses. Moreover, the advancement of tabular GAN architectures addresses the specific challenges encountered in synopsis construction. These advanced GAN variations exhibit a promising capacity to generate high-fidelity synopses, potentially transforming the efficiency and effectiveness of AQP in data-driven systems. 
  • 573
  • 25 Jan 2024
Topic Review
Deep Learning Networks and YOHO English Speech Dataset
The rapid momentum of deep neural networks (DNNs) has yielded state-of-the-art performance in various machine-learning tasks using speaker identification systems. Speaker identification is based on the speech signals and the features that can be extracted from them.
  • 571
  • 07 Sep 2023
Topic Review
Matrix Factorization Recommendation Algorithm Based on Attention Interaction
Recommender systems are widely used in e-commerce, movies, music, social media, and other fields because of their personalized recommendation functions. The recommendation algorithm is used to capture user preferences, item characteristics, and the items that users are interested in are recommended to users.
  • 571
  • 26 Feb 2024
Topic Review
Hybrid Multi-Label Classification Model for Medical Applications
Multi-label classification is typically used in different data mining applications, like labeling videos, images, music, and texts. Multi-label classification classifies documents into various classes simultaneously based on their properties.
  • 570
  • 16 Aug 2023
Topic Review
Hybrid Deep Belief Network in Traffic Flow Prediction
Accurate and timely traffic flow prediction not just allows traffic controllers to evade traffic congestion and guarantee standard traffic functioning, it even assists travelers to take advantage of planning ahead of schedule and modifying travel routes promptly. The presented hybrid deep belief network (AST2FP-OHDBN) model initially normalizes the traffic data using min–max normalization.
  • 569
  • 21 Nov 2022
Topic Review
Deepfake Attacks
Deepfakes, is a fast-developing field at the nexus of artificial intelligence and multimedia. These artificial media creations, made possible by deep learning algorithms, allow for the manipulation and creation of digital content that is extremely realistic and challenging to identify from authentic content. Deepfakes can be used for entertainment, education, and research; however, they pose a range of significant problems across various domains, such as misinformation, political manipulation, propaganda, reputational damage, and fraud. 
  • 569
  • 08 Dec 2023
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