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:
Hottest Latest Alphabetical (A-Z) Alphabetical (Z-A)
Type:
All Topic Review Biography
Topic Review
A Sub-Second Method for SAR Image Registration
For Synthetic Aperture Radar (SAR) image registration, successive processes following feature extraction are required by both the traditional feature-based method and the deep learning method. Among these processes, the feature matching process—whose time and space complexity are related to the number of feature points extracted from sensed and reference images, as well as the dimension of feature descriptors—proves to be particularly time consuming. Additionally, the successive processes introduce data sharing and memory occupancy issues, requiring an elaborate design to prevent memory leaks.
  • 235
  • 24 Oct 2023
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
  • 328
  • 01 Nov 2023
Topic Review
A Systematic Approach to Healthcare Knowledge Management Systems
Big data in healthcare contain a huge amount of tacit knowledge that brings great value to healthcare activities such as diagnosis, decision support, and treatment. However, effectively exploring and exploiting knowledge on such big data sources exposes many challenges for both managers and technologists. A healthcare knowledge management system that ensures the systematic knowledge development process on various data in hospitals was proposed. It leverages big data technologies to capture, organize, transfer, and manage large volumes of medical knowledge, which cannot be handled with traditional data-processing technologies. In addition, machine-learning algorithms are used to derive knowledge at a higher level in supporting diagnosis and treatment.
  • 1.2K
  • 13 May 2022
Topic Review
A Tangible VR-Based Interactive System for Intergenerational Learning
The recent years have witnessed striking global demographic shifts. Retired elderly people often stay home, seldom communicate with their grandchildren, and fail to acquire new knowledge or pass on their experiences.  Digital technologies based on virtual reality (VR) with tangible user interfaces (TUIs) were introduced into the design of a novel interactive system for intergenerational learning, aimed at promoting the elderly people’s interactions with younger generations.
  • 378
  • 31 May 2022
Topic Review
A Taxonomic Survey of Physics-Informed Machine Learning
Physics-informed machine learning (PIML) refers to the emerging area of extracting physically relevant solutions to complex multiscale modeling problems lacking sufficient quantity and veracity of data with learning models informed by physically relevant prior information.
  • 305
  • 20 Jun 2023
Topic Review
A Unified Framework for RGB-Infrared Transfer
Infrared(IR) images (both 0.7-3 µm and 8-15 µm) offer radiation intensity texture information that visible images lack, making them particularly helpful in daytime, nighttime, and complex scenes. Many researchers are studying how to translate RGB images into infrared images for deep learning-based visual tasks such as object tracking, crowd counting, panoramic segmentation, and image fusion in urban scenarios. The utilization of the RGB-IR dataset in the aforementioned tasks holds the potential to provide comprehensive multi-band fusion data for urban scenes, thereby facilitating precise modeling across different scenarios. In addressing the challenge of accurately generating high-radiance textures for the targets in the infrared spectrum, the proposed approach aims to ensure alignment between the generated infrared images and the radiation feature of ground-truth IR images.
  • 253
  • 18 Dec 2023
Topic Review
Abnormal Activity Recognition for Visual Surveillance
Due to the ever increasing number of closed circuit television (CCTV) cameras worldwide, it is the need of the hour to automate the screening of video content. Still, the majority of video content is manually screened to detect some anomalous incidence or activity. Automatic abnormal event detection such as theft, burglary, or accidents may be helpful in many situations. However, there are significant difficulties in processing video data acquired by several cameras at a central location, such as bandwidth, latency, large computing resource needs, and so on. 
  • 216
  • 11 Jan 2024
Topic Review
Abstract Entity Patterns for Sensors and Actuators
Sensors and actuators are fundamental units in Cyber–Physical and Internet of Things systems. Because they are included in a variety of systems, using many technologies, it is very useful to characterize their functions abstractly by describing them as Abstract Entity Patterns (AEPs), which are patterns that describe abstract conceptual entities.
  • 385
  • 19 May 2023
Topic Review
Abstract Syntax Notation One
Abstract Syntax Notation One (ASN.1) is a standard interface description language for defining data structures that can be serialized and deserialized in a cross-platform way. It is broadly used in telecommunications and computer networking, and especially in cryptography. Protocol developers define data structures in ASN.1 modules, which are generally a section of a broader standards document written in the ASN.1 language. The advantage is that the ASN.1 description of the data encoding is independent of a particular computer or programming language (other than ASN.1.) Because ASN.1 is both human-readable and machine-readable, an ASN.1 compiler can compile modules into libraries of code, CODECs, that decode or encode the data structures. Some ASN.1 compilers can produce code to encode or decode several encodings, e.g. packed, BER or XML. ASN.1 is a joint standard of the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) and ISO/IEC, originally defined in 1984 as part of CCITT X.409:1984. In 1988, ASN.1 moved to its own standard, X.208, due to wide applicability. The substantially revised 1995 version is covered by the X.680 series. The latest revision of the X.680 series of recommendations is the 5.0 Edition, published in 2015.
  • 1.0K
  • 04 Nov 2022
Topic Review
Abstractive vs. Extractive Summarization
Due to the huge and continuously growing size of the textual corpora existing on the Internet, important information may go unnoticed or become lost. At the same time, the task of summarizing these resources by human experts is tedious and time consuming. This necessitates the automation of the task. Natural language processing (NLP) is a multidisciplinary research field, merging aspects and approaches from computer science, artificial intelligence and linguistics; it deals with the development of processes that semantically and efficiently analyze vast amounts of textual data. Text summarization (TS) is a fundamental NLP subtask, which has been defined as the process of the automatic creation of a concise and fluent summary that captures the main ideas and topics of one or multiple documents.
  • 650
  • 07 Jul 2023
  • Page
  • of
  • 371
Featured Entry Collections
>>

Featured Books

>>
Encyclopedia of Social Sciences
Encyclopedia of COVID-19
Encyclopedia of Fungi
Encyclopedia of Digital Society, Industry 5.0 and Smart City
Video Production Service
Feedback