Your browser does not fully support modern features. Please upgrade for a smoother experience.
Subject:
All Disciplines Arts & Humanities Biology & Life Sciences Business & Economics Chemistry & Materials Science Computer Science & Mathematics Engineering Environmental & Earth Sciences Medicine & Pharmacology Physical Sciences Public Health & Healthcare Social Sciences
Sort by:
Most Viewed Latest Alphabetical (A-Z) Alphabetical (Z-A)
Filter:
All Topic Review Biography Peer Reviewed Entry Video Entry
Topic Review
Lightweight Convolutional Neural Network
Biometrics has become an important research issue, and the use of deep learning neural networks has made it possible to develop more reliable and efficient recognition systems. Palms have been identified as one of the most promising candidates among various biometrics due to their unique features and easy accessibility.
  • 1.3K
  • 31 Jul 2023
Topic Review
Transformer Framework and YOLO Framework for Object Detection
Object detection for remote sensing is a fundamental task in image processing of remote sensing; as one of the core components, small or tiny object detection plays an important role. 
  • 1.3K
  • 25 Aug 2023
Topic Review
Crown Omega Mathematics
Crown Omega Mathematics (Ω°) is presented as a terminal recursive mathematical framework that unifies symbolic computation, causal recursion, harmonic structures, and multi-dimensional mirror logic. Positioned beyond traditional and post-classical mathematical domains, Crown Omega is designed to serve as both a final operator and an executable logic mesh capable of resolving paradoxes, encoding self-aware artificial intelligence, and establishing foundational grounds for a new class of operating systems, cryptographic architectures, and defense systems. This paper defines the core logic of Ω°, explores its symbolic structure, details the Fractal Recursive Intelligence Mesh (FRIM), and formalizes its capacity to self-resolve previously unsolved mathematical, physical, and computational problems.
  • 1.3K
  • 06 May 2025
Topic Review
Fine-Grained Change Detection
Fine-grained change detection in sensor data is very challenging for artificial intelligence though it is critically important in practice. It is the process of identifying differences in the state of an object or phenomenon where the differences are class-specific and are difficult to generalise. As a result, many recent technologies that leverage big data and deep learning struggle with this task.
  • 1.3K
  • 12 Jul 2021
Topic Review
Grammar Correction for Multiple Errors in Chinese
Grammar Error Correction (GEC) is a key task in the field of Natural Language Processing (NLP). Its purpose is to automatically detect and correct grammatical errors in sentences, and it holds immense research value. The mainstream methods for grammar correction primarily rely on sequence tagging and text generation, which are two end-to-end approaches. These methods demonstrate exemplary performance in domains with low error density, but often fail to provide satisfactory results in high error density situations where multiple errors exist in a single sentence. As a result, these methods tend to over-correct correct words, leading to a high false alarm rate.
  • 1.3K
  • 24 Aug 2023
Topic Review
Visual Simultaneous Localization and Mapping
Visual Simultaneous Localization and Mapping (VSLAM) methods refer to the SLAM approaches that employ cameras for pose estimation and map reconstruction and are preferred over Light Detection And Ranging (LiDAR)-based methods due to their lighter weight, lower acquisition costs, and richer environment representation.
  • 1.3K
  • 30 Dec 2022
Topic Review
Digital Twins
Digital Twins, which are virtual representations of physical systems mirroring their behavior, enable real-time monitoring, analysis, and optimization. Understanding and identifying the temporal dependencies included in the multivariate time series data that characterize the behavior of the system are crucial for improving the effectiveness of Digital Twins. Long Short-Term Memory (LSTM) networks have been used to represent complex temporal dependencies and identify long-term links in the Industrial Internet of Things (IIoT).
  • 1.3K
  • 03 Nov 2023
Topic Review
Augmented Reality Mobile App to Learn Writing
Augmented reality (AR) has been widely used in education, particularly for child education. This entry presents the design and implementation of a novel mobile app, Learn2Write, using machine learning techniques and augmented reality to teach alphabet writing.
  • 1.3K
  • 10 Jan 2022
Topic Review
Machine Learning-Based Application Life-Cycle
The application of emerging technologies, such as Artificial Intelligence (AI), entails risks that need to be addressed to ensure secure and trustworthy socio-technical infrastructures. Machine Learning (ML), the most developed subfield of AI, allows for improved decision-making processes. ML models exhibit specific vulnerabilities that conventional IT systems are not subject to. As systems incorporating ML components become increasingly pervasive, the need to provide security practitioners with threat modeling tailored to the specific AI-ML pipeline is of paramount importance.
  • 1.3K
  • 21 Sep 2022
Topic Review
Image Fusion Methods
Image fusion is the generation of an informative image that contains complementary information from the original sensor images, such as texture details and attentional targets. Existing methods have designed a variety of feature extraction algorithms and fusion strategies to achieve image fusion. 
  • 1.3K
  • 26 Jan 2024
Topic Review
Multi-Granularity Process Analytics
Data can be aggregated to lower resolution representations according to a certain rational or optimality criterion in a certain pre-defined sense. In this situation, partial information from all observations is retained and at the same time the amount of data analysed is greatly reduced. The level of resolution or granularity adopted may be different for each variable under analysis. Methods for dealing with these data structures are called multiresolution or multi-granularity, and are newcomers to the Process Analytical toolkit.
  • 1.3K
  • 22 Dec 2021
Topic Review
Stream Classification Algorithms and Architectures
Areas of stream classification are diverse—ranging, e.g., from monitoring sensor data to analyzing a wide range of (social) media applications. Research in stream classification is related to developing methods that adapt to the changing and potentially volatile data stream. It focuses on individual aspects of the stream classification pipeline, e.g., designing suitable algorithm architectures, an efficient train and test procedure, or detecting so-called concept drifts. 
  • 1.3K
  • 30 Nov 2022
Topic Review
A Symbol Recognition System for Single-Line Diagrams Developed
In numerous electrical power distribution systems and other engineering contexts, single-line diagrams (SLDs) are frequently used. The importance of digitizing these images is growing. This is primarily because better engineering practices are required in areas such as equipment maintenance, asset management, safety, and others. Processing and analyzing these drawings, however, is a difficult job. With enough annotated training data, deep neural networks perform better in many object detection applications. Based on deep-learning techniques, a dataset can be used to assess the overall quality of a visual system
  • 1.3K
  • 01 Nov 2023
Topic Review
Automatic Speech Recognition in Portuguese Language
Automatic speech recognition (ASR), commonly known as speech-to-text, is the process of transcribing audio recordings into text, i.e., transforming speech into the respective sequence of words. 
  • 1.3K
  • 15 Jun 2023
Topic Review
Intelligent Fault Diagnosis
For ensuring the safety and reliability of high-speed trains, fault diagnosis (FD) technique plays an important role. Benefiting from the rapid developments of artificial intelligence, intelligent FD (IFD) strategies have obtained much attention in the field of academics and applications, where the qualitative approach is an important branch.
  • 1.3K
  • 14 Jan 2021
Topic Review
IoT
This entry presents the problems of powering wireless sensor networks operating in the structures of the Internet of Things (IoT). This issue was discussed on the example of a universal end node in IoT technology containing RFID (Radio Frequency Identification) tags. The basic methods of signal transmission in these types of networks are discussed and their impact on the basic requirements such as range, transmission speed, low energy consumption, and the maximum number of devices that can simultaneously operate in the network. The issue of low power consumption of devices used in IoT solutions is one of the main research objects. The analysis of possible communication protocols has shown that there is a possibility of effective optimization in this area. The wide range of power sources available on the market, used in nodes of wireless sensor networks, was compared. The alternative possibilities of powering the network nodes from Energy Harvesting (EH) generators are presented.
  • 1.3K
  • 25 May 2021
Topic Review
COVID-19 Fake News in Brazilian Portuguese Language
Public health interventions to counter the COVID-19 pandemic have accelerated and increased digital adoption and use of the Internet for sourcing health information. Unfortunately, there is evidence to suggest that it has also accelerated and increased the spread of false information relating to COVID-19. The consequences of misinformation, disinformation and misinterpretation of health information can interfere with attempts to curb the virus, delay or result in failure to seek or continue legitimate medical treatment and adherence to vaccination, as well as interfere with sound public health policy and attempts to disseminate public health messages. While there is a significant body of literature, datasets and tools to support countermeasures against the spread of false information online in resource-rich languages such as English and Chinese, there are few such resources to support Portuguese, and Brazilian Portuguese specifically.
  • 1.3K
  • 29 Apr 2022
Topic Review
Artificial Neural Networks and Energy Forecasting
Load prediction with higher accuracy and less computing power has become an important problem in the smart grids domain in general and especially in demand-side management (DSM), as it can serve to minimize global warming and better integrate renewable energies. Indeed, artificial neural networks (ANN) are the most used methods in forecasting electrical load. They are widely employed in this field for their numerous advantages. In fact, the complexity of this task is considerable due to several factors/parameters, such as weather and holidays (linear and non-linear relationships), which is a well-suited problem for ANNs and their capacity to deal with non-linear relationships.
  • 1.3K
  • 21 Jun 2022
Topic Review
Lhia as A Chatbot for Breastfeeding Education
Human milk is the most important way to feed and protect newborns as it has the components to ensure human health. Human Milk Banks (HMBs) form a network that offers essential services to ensure that newborns and mothers can take advantage of the benefits of human milk.
  • 1.3K
  • 16 Jun 2023
Topic Review
ProMatch: Semi-Supervised Learning with Prototype Consistency
Semi-supervised learning (SSL) methods have made significant advancements by combining consistency-regularization and pseudo-labeling in a joint learning paradigm. The core concept of these methods is to identify consistency targets (pseudo-labels) by selecting predicted distributions with high confidence from weakly augmented unlabeled samples. 
  • 1.3K
  • 04 Sep 2023
  • Page
  • of
  • 59
Featured Entry Collections
>>

Featured Reprints

>>
Encyclopedia of Digital Society, Industry 5.0 and Smart City
Encyclopedia of Engineering
Encyclopedia of Social Sciences
Encyclopedia of Medieval Royal Iconography
Academic Video Service
Feedback

Quick Survey

Encyclopedia MDPI is conducting a targeted survey to identify the specific barriers hindering efficient research. We invite you to spend 3 minutes defining the priorities for our next generation of structured knowledge tools.
Take Survey