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Topic Review
Knowledge Graph Entity Alignment
The objective of the entity alignment (EA) task is to identify entities with identical semantics across distinct knowledge graphs (KGs) situated in the real world, which has garnered extensive recognition in both academic and industrial circles.
  • 842
  • 31 May 2023
Topic Review
Fire Detection Based on Deep Learning Approaches
The field of image recognition has witnessed the rise of a particular type of deep neural network (DNN), CNN. Learnable neural networks comprise numerous layers, each of which performs a separate function when extracting or identifying features. Computer vision, a compelling form of AI, is ubiquitous, and is often experienced without us realizing it. Image processing is the area of computer vision and science devoted to imitating elements of the human visual system and enabling computers to discern and process objects in images and videos similarly to humans. Several deep learning (DL) techniques have been effectively applied in various fields of fire and face detection research.
  • 839
  • 02 Jan 2024
Topic Review
Greylisting
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.
  • 838
  • 14 Oct 2022
Topic Review
DetectFormer
Object detection plays a vital role in autonomous driving systems, and the accurate detection of surrounding objects can ensure the safe driving of vehicles. A category-assisted transformer object detector called DetectFormer for autonomous driving. The proposed object detector can achieve better accuracy compared with the baseline. Specifically, ClassDecoder is assisted by proposal categories and global information from the Global Extract Encoder (GEE) to improve the category sensitivity and detection performance. This fits the distribution of object categories in specific scene backgrounds and the connection between objects and the image context. Data augmentation is used to improve robustness and attention mechanism added in backbone network to extract channel-wise spatial features and direction information.
  • 837
  • 15 Jul 2022
Topic Review
Deep Learning Models in Video Deepfake Detection
The increasing use of deep learning techniques to manipulate images and videos, commonly referred to as “deepfakes”, is making it more challenging to differentiate between real and fake content, while various deepfake detection systems have been developed, they often struggle to detect deepfakes in real-world situations. In particular, these methods are often unable to effectively distinguish images or videos when these are modified using novel techniques which have not been used in the training set.
  • 835
  • 22 May 2023
Topic Review
FCAN–XGBoost
Emotion recognition has broad application prospects in fields such as artificial intelligence (AI), intelligent healthcare, remote education, and virtual reality (VR) games. Accurately recognizing human emotions is one of the most urgent issues in the brain–computer interface. FCAN XGBoost is a electroencephalogram (EEG) based emotion recognition model that can quickly and accurately recognize four types of emotions in EEG.
  • 834
  • 05 Sep 2023
Topic Review
ADX (File Format)
CRI ADX is a lossy proprietary audio storage and compression format developed by CRI Middleware specifically for use in video games; it is derived from ADPCM. Its most notable feature is a looping function that has proved useful for background sounds in various games that have adopted the format, including many games for the Sega Dreamcast as well as some PlayStation 2, GameCube and Wii games. One of the first games to use ADX was Burning Rangers, on the Sega Saturn. Notably, the Sonic the Hedgehog series from the Dreamcast generation up to at least Shadow the Hedgehog have used this format for sound and voice recordings. Jet Set Radio Future for original Xbox also used this format. On top of the main ADPCM encoding, the ADX toolkit also includes a sibling format, AHX, which uses a variant of MPEG-2 audio intended specifically for voice recordings and a packaging archive, AFS, for bundling multiple CRI ADX and AHX tracks into a single container file. Version 2 of the format (ADX2) uses the HCA and HCA-MX extension, which are usually bundled into a container file with the extensions ACB and AWB. The AWB extension is not to be confused with the Audio format with the same extension and mostly contains the binary data for the HCA files.
  • 832
  • 29 Sep 2022
Topic Review
Federated Learning Based on Deep Reinforcement Learning
Federated learning (FL) is a distributed machine learning paradigm that enables a large number of clients to collaboratively train models without sharing data.
  • 832
  • 24 Nov 2023
Topic Review
Artificial Intelligence Course Design Planning Framework
The use of Artificial Intelligence (AI) has become key in numerous domains, emphasizing the need for education in this field. The interdisciplinary nature of AI and its relevance across various sectors call for an integration of AI topics into university curricula. This article introduces the "AI Course Design Planning Framework", a comprehensive tool designed to structure the development of domain-specific AI courses at the university level. The AI Course Design Planning Framework forms a visual and practical tool for instructors and course developers in the higher education or professional education context with a special focus on non-computer science (non-CS) students. It can be used as a means to gather ideas, innovate, plan and communicate ideas for domain-specific AI courses. The framework can be used as a self-contained instrument for individuals, in tandem with AI and domain experts or in a workshop setting with multiple people. Scholars suggest filling it from left to right, first considering the questions on AI in the domain, the learning environment of the course and last, the course implementation.
  • 831
  • 06 Dec 2023
Topic Review
Speech Emotion Recognition
Speech is the most natural way of human communication. Affective computing systems based on speech play an important role in promoting human–computer interaction, and emotion recognition is the first step. Due to the lack of a precise definition of emotion and the inclusive and complex influence of emotion generation and expression, accurately recognizing speech emotions is still difficult. Speech emotion recognition (SER) is an important problem that is receiving increasing interest from researchers due to its numerous applications, such as e-learning, clinical trials, audio monitoring/surveillance, lie detection, entertainment, video games, and call centers.
  • 830
  • 25 Jan 2024
Topic Review
An Improved Modulation Recognition Algorithm
Modulation recognition is an important technology in wireless communication systems. Deep learning-based modulation recognition algorithms, which can autonomously learn deep features and achieve superior recognition performance compared with traditional algorithms.
  • 828
  • 19 May 2023
Topic Review
Types of Dimension Reduction Techniques
Hybridization is the most widely used modification technique for the dimension reduction problem. There are three types of hybridization: integrating a nature-inspired algorithm with another nature-inspired algorithm, integrating a nature-inspired algorithm with a classifier, and integrating a nature-inspired algorithm with filter or extraction techniques.
  • 827
  • 17 Mar 2023
Topic Review
AI and Neural Network Algorithms
Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into the daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a num- ber of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active development of artificial intelligence (AI) and neural networks. A neural algorithm application in Micro-Electro-Mechanical System microcantilever biosensors is anticipated through the associated application of the principal com-ponent analysis approach. Researchers investigation has more scientific study value, because there are currently no favorable reports on the market regarding the use of AI with Micro-Electro-Mechanical System microcantilever sensors.
  • 825
  • 13 Sep 2022
Topic Review
Malware Detection Method for with ViT Attention Mechanism
Artificial intelligence (AI) is increasingly being utilized in cybersecurity, particularly for detecting malicious applications. However, the black-box nature of AI models presents a significant challenge. This lack of transparency makes it difficult to understand and trust the results. In order to address this, it is necessary to incorporate explainability into the detection model. There is insufficient research to provide reasons why applications are detected as malicious or explain their behavior.
  • 824
  • 24 Jul 2023
Topic Review
AI-Informed Decision Making
AI-assisted decision-making that impacts individuals raises critical questions about transparency and fairness in artificial intelligence (AI). Much research has highlighted the reciprocal relationships between the transparency/explanation and fairness in AI-assisted decision-making. Thus, considering their impact on user trust or perceived fairness simultaneously benefits responsible use of socio-technical AI systems, but currently receives little attention.
  • 822
  • 01 Jul 2022
Topic Review
Routing Services in Smart Cities
The vehicle routing problem (VRP) is a complex optimization problem, in which there exists a set of clients at various locations, each one with a shipment need, and a fleet of vehicles, departing from the central depot that shall optimally satisfy the needs of the clients. The aim of a typical VRP is to find out the optimal route to minimize the total costs. Furthermore, various factors affecting route planning, such as vehicle capacity, fuel consumption, traffic congestion, etc., have to be considered to accomplish the minimization of the total route costs.
  • 821
  • 31 Jan 2023
Topic Review
Wind–Solar Hybrid System Modeling
Wind–solar hybrid systems combine solar photovoltaic cells and wind turbines to produce power from both solar and wind energy.
  • 819
  • 31 May 2023
Topic Review
Multilevel Distribution Propagation Network
A two-stage framework based on the distribution propagation graph neural network (DPGN) called the multilevel distribution propagation network (MDPN). An instance-segmentation-based object localization (ISOL) module and a graph-based multilevel distribution propagation (GMDP) module are both included in the MDPN.
  • 819
  • 05 Jul 2023
Topic Review
Graph Clustering Algorithms
Graph clustering has received considerable attention, and its applications are numerous, ranging from the detection of social communities to the clustering of computer networks. It is classified as an NP-class problem, and several algorithms have been proposed with specific objectives. There also exist various quality metrics for evaluating them. Having clusters with the required density can be beneficial because it permits the effective deployment of resources.
  • 819
  • 26 Jan 2024
Topic Review
Domain Name System-based Blackhole List
A Domain Name System-based blackhole list, Domain Name System blacklist (DNSBL) or real-time blackhole list (RBL) is a service for operation of mail servers to perform a check via a Domain Name System (DNS) query whether a sending host's IP address is blacklisted for email spam. Most mail server software can be configured to check such lists, typically rejecting or flagging messages from such sites. A DNSBL is a software mechanism, rather than a specific list or policy. Dozens of DNSBLs exist. They use a wide array of criteria for listing and delisting addresses. These may include listing the addresses of zombie computers or other machines being used to send spam, Internet service providers (ISPs) who willingly host spammers, or those which have sent spam to a honeypot system. Since the creation of the first DNSBL in 1998, the operation and policies of these lists have frequently been controversial, both in Internet advocacy circles and occasionally in lawsuits. Many email systems operators and users consider DNSBLs a valuable tool to share information about sources of spam, but others including some prominent Internet activists have objected to them as a form of censorship. In addition, a small number of DNSBL operators have been the target of lawsuits filed by spammers seeking to have the lists shut down.
  • 818
  • 14 Nov 2022
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