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Topic Review
Sequence-Based Recommendation System
Sequence-based models have various applications in recommendation systems; these models recommend the interested items of the user according to the user’s behavioral sequence. However, sequence-based models have a limitation of length. When the length of the user’s behavioral sequence exceeds the limitation of the model, the model cannot take advantage of the complete behavioral sequence of the user and cannot know the user’s holistic interests. The accuracy of the model then goes down. Meanwhile, sequence-based models only pay attention to the sequential signals of the data but do not pay attention to the spatial signals of the data, which will also affect the model’s accuracy.
  • 713
  • 12 Jan 2024
Topic Review
Spatial and Temporal Hierarchy for Autonomous Navigation
Robust evidence suggests that humans explore their environment using a combination of topological landmarks and coarse-grained path integration. This approach relies on identifiable environmental features (topological landmarks) in tandem with estimations of distance and direction (coarse-grained path integration) to construct cognitive maps of the surroundings. This cognitive map is believed to exhibit a hierarchical structure, allowing efficient planning when solving complex navigation tasks.
  • 713
  • 29 Jan 2024
Topic Review
Peripheral Blood Smears Examination by Artificial Intelligence
Artificial intelligence (AI) has emerged as a cutting-edge tool, simultaneously accelerating, securing, and enhancing the diagnosis and treatment of patients. An exemplification of this capability is evident in the analysis of peripheral blood smears (PBS). In university medical centers, hematologists routinely examine hundreds of PBS slides daily to validate or correct outcomes produced by advanced hematology analyzers assessing samples from potentially problematic patients. This process may logically lead to erroneous PBC readings, posing risks to patient health. AI functions as a transformative tool, significantly improving the accuracy and precision of readings and diagnoses.
  • 712
  • 27 Dec 2023
Topic Review
Efficient Detection of Forest Fire Smoke
Forest fires are a significant environmental threat, causing loss of biodiversity, alteration of ecosystems, and impacting human lives and properties. Early detection is critical for effective firefighting and minimizing damages. Smoke detection plays an indispensable role in the early monitoring of forest fires. Its rapid dispersion, visibility, and integration with contemporary sensor technologies render it not only an effective complement but also a potential substitute for flame monitoring. In this context, various forest fire smoke detection methods and systems have been developed. These methods include satellite-based smoke detection, ground-based sensors for smoke detection, and UAV-based detection, each with its unique approach, advantages, and limitations. Moreover, image processing technology occupies a crucial position in the detection of forest fire smoke.
  • 711
  • 27 Dec 2023
Topic Review
Safety in Traffic Management Systems
Traffic management systems play a vital role in ensuring safe and efficient transportation on roads. However, the use of advanced technologies in traffic management systems has introduced new safety challenges. Therefore, it is important to ensure the safety of these systems to prevent accidents and minimize their impact on road users.
  • 710
  • 20 Oct 2023
Topic Review
Use of Self-Supervised Learning against DDoS Attacks
The Internet of Things (IoT), projected to exceed 30 billion active device connections globally by 2025, presents an expansive attack surface. The frequent collection and dissemination of confidential data on these devices exposes them to significant security risks, including user information theft and denial-of-service attacks.
  • 710
  • 24 Nov 2023
Topic Review
Crack Detection and Segmentation in Concrete Structures
To prevent potential instability, the early detection of cracks is imperative due to the prevalent use of concrete in critical infrastructure. Automated techniques leveraging artificial intelligence, machine learning, and deep learning as the traditional manual inspection methods are time-consuming. The existing automated concrete crack detection algorithms, despite recent advancements, face challenges in robustness, particularly in precise crack detection amidst complex backgrounds and visual distractions, while also maintaining low inference times.
  • 710
  • 24 Jan 2024
Topic Review
IoMT Based Big Data Framework for COVID-19
The Internet of Medical Things (IoMT) is transforming modern healthcare systems by merging technological, economical, and social opportunities and has recently gained traction in the healthcare domain. The severely contagious respiratory syndrome coronavirus called COVID-19 has emerged as a severe threat to public health. COVID-19 is a highly infectious virus that is spread by person-to-person contact.
  • 705
  • 22 Sep 2023
Topic Review
Neural Load Disaggregation
Non-intrusive load monitoring (NILM) techniques are central techniques to achieve the energy sustainability goals through the identification of operating appliances in the residential and industrial sectors, potentially leading to increased rates of energy savings. NILM received significant attention, reflected by the number of contributions and systematic reviews published yearly.
  • 702
  • 09 Feb 2023
Topic Review
NextDet with Attentive Feature Aggregation
NextDet, built upon YOLOv5 object detection framework for efficient monocular sparse-to-dense streaming perception, is specially designed for autonomous vehicles and autonomous rovers using edge devices. NextDet is faster, lighter and can perform both, sparse and dense object detection efficiently.
  • 701
  • 30 Aug 2023
Topic Review
Encoder–Decoder Architecture and Kernel-Sharing Mechanism
As the application of unmanned aerial vehicles (UAVs) becomes more and more widespread, accidents such as accidental injuries to personnel, property damage, and loss and destruction of UAVs due to accidental UAV crashes also occur in daily use scenarios. To reduce the occurrence of such accidents, UAVs need to have the ability to autonomously choose a safe area to land in an accidental situation, and the key lies in realizing on-board real-time semantic segmentation processing.
  • 701
  • 18 Feb 2024
Topic Review
Machine Learning and Eye-Tracking Technology in ASD
Early and objective autism spectrum disorder (ASD) assessment, as well as early intervention are particularly important and may have long term benefits in the lives of ASD people. ASD assessment relies on subjective rather on objective criteria, whereas advances in research point to up-to-date procedures for early ASD assessment comprising eye-tracking technology, machine learning, as well as other assessment tools. This systematic review, the first to our knowledge of its kind, provides a comprehensive discussion of 30 studies irrespective of the stimuli/tasks and dataset used, the algorithms applied, the eye-tracking tools utilised and their goals. Evidence indicates that the combination of machine learning and eye-tracking technology could be considered a promising tool in autism research regarding early and objective diagnosis.
  • 700
  • 14 Dec 2021
Topic Review
Park Supplementary Review System
When planning a travel or an adventure, sightseers increasingly rely on opinions posted on the Internet tourism related websites, such as TripAdvisor, Booking.com or Expedia. Unfortunately, beautiful, yet less-known places and rarely visited sightspots often do not accumulate sufficient number of valuable opinions on such websites. An approach is developed  consisting of a system (PSRS) for wildlife sightspots and propose a method for verifying collected geotagged tweets and using them as on-spot reviews. 
  • 700
  • 07 Mar 2022
Topic Review
Requirements of Edge Machine Learning
The union of Edge Computing (EC) and Artificial Intelligence (AI) has brought forward the Edge AI concept to provide intelligent solutions close to the end-user environment, for privacy preservation, low latency to real-time performance, and resource optimization. 
  • 700
  • 27 Sep 2023
Topic Review
Deep Learning in Medical Imaging Segmentation
Deep learning algorithms were applied to serve the purpose as a diagnostic tool and applied to Computed Tomography (CT) scan images of the ovarian region. The images went through a series of pre-processing techniques and, further, the tumour was segmented using the UNet model. The instances were then classified into two categories—benign and malignant tumours. 
  • 699
  • 04 Aug 2023
Topic Review
Deep Learning Methods of Small Object Detection
Remote sensing methodology has been increasingly applied in fields such as forest fire detection, iceberg detection, ship detection, floating object detection, and agriculture monitoring. Synthetic aperture radar (SAR) images can be used to construct two-dimensional images, which can be further reconstructed into multidimensional images if necessary. When the SAR focuses on the target application, such as biomass detection in the forest, ship detection in the ocean, and vehicle count on land, it comprises many small objects. Detecting these small images is less effortless than general object detection in typical images.
  • 695
  • 14 Jul 2023
Topic Review
Sign-Language Detection
Sign language is the most commonly used form of communication for persons with disabilities who have hearing or speech difficulties. However, persons without hearing impairment cannot understand these signs in many cases. As a consequence, persons with disabilities experience difficulties while expressing their emotions or needs. Thus, a sign character detection and text generation system is necessary to mitigate this issue.
  • 695
  • 25 Oct 2023
Topic Review
Vision-Based Flying Obstacle Detection for Avoiding Midair Collisions
See and avoid is a basic procedure that pilots must learn and apply during flight. Various technologies have been introduced to avoid midair collisions, but accidents still occur because they are neither mandatory in all airspaces nor suitable for all aircraft.
  • 695
  • 26 Oct 2023
Topic Review
Plant-Parasitic Nematode
Plant-parasitic nematodes (PPN), especially sedentary endoparasitic nematodes like root-knot nematodes (RKN), pose a significant threat to major crops and vegetables. They are responsible for causing substantial yield losses, leading to economic consequences, and impacting the global food supply. The identification of PPNs and the assessment of their population is a tedious and time-consuming task.
  • 695
  • 31 Jan 2024
Topic Review
Greylisting (Email)
Greylisting is a method of defending e-mail users against spam. A mail transfer agent (MTA) using greylisting will "temporarily reject" any email from a sender it does not recognize. If the mail is legitimate, the originating server will try again after a delay, and if sufficient time has elapsed, the email will be accepted.
  • 694
  • 01 Nov 2022
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