Artificial Intelligence and Pattern Recognition, Vision, Learning

2020 ◽  
pp. 337-364
Author(s):  
Isabelle Bloch ◽  
Régis Clouard ◽  
Marinette Revenu ◽  
Olivier Sigaud
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition

Principles of induction and approaches to attribute based induction

1991 ◽  
Vol 6 (4) ◽  
pp. 307-333 ◽  
Author(s):  
G. Kalkanis ◽  
G. V. Conroy
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Cognitive Psychology ◽  
Expert Systems ◽  
Basic Principles ◽  
Inductive Approach ◽  
Induction Process

AbstractThis paper presents a survey of machine induction, studied mainly from the field of artificial intelligence, but also from the fields of pattern recognition and cognitive psychology. The paper consists of two parts: Part I discusses the basic principles and features of the machine induction process; Part II uses these principles and features to review and criticize the major supervised attribute-based induction methods. Attribute-based induction has been chosen because it is the most commonly used inductive approach in the development of expert systems and pattern recognition models.

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence

2020 ◽  
Vol 24 (01) ◽  
pp. 38-49 ◽  
Author(s):  
Natalia Gorelik ◽  
Jaron Chong ◽  
Dana J. Lin
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Bone Tumors ◽  
Image Interpretation ◽  
Bone Age ◽  
Musculoskeletal Imaging ◽  
Radiology Workflow ◽  
Disease Response ◽  
Osseous Metastases ◽  
Applications Of Ai

AbstractArtificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect and characterize abnormalities as well as monitor disease response. Many AI-based image interpretation tasks for musculoskeletal (MSK) pathologies have been studied, including the diagnosis of bone tumors, detection of osseous metastases, assessment of bone age, identification of fractures, and detection and grading of osteoarthritis. This article explores the applications of AI for image interpretation of MSK pathologies.

scholarly journals Foreword to the special issue on recent advances on pattern recognition and artificial intelligence

2018 ◽  
Vol 29 (1) ◽  
pp. 1-2 ◽  
Author(s):  
Huawen Liu ◽  
Jianping Yin ◽  
Xudong Luo ◽  
Shichao Zhang
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Special Issue ◽  
Recent Advances

A Novel Artificial Face Mask based Nanofibers with Special Intelligent Engineered Nanocomposite Against Covid-19

2021 ◽  
pp. PP. 21-22
Author(s):  
Ahmed A. Elngar ◽  
◽  
◽  
S.I. El El-Dek
Keyword(s):  
Artificial Intelligence ◽  
Resource Allocation ◽  
Pattern Recognition ◽  
Disease Management ◽  
Face Mask ◽  
Vital Role ◽  
Mobile Unit ◽  
Disease Clusters ◽  
Infected People ◽  
The Face

We introduce our idea about a new face mask against Covid-19. Herein our novel face mask is a polymeric matrix of nanofibers. These nanofibers are decorated with special engineered nanocomposite. The later possesses antiviral, antimicrobial. A well-established IR temperature biosensor will be implanted in the face mask and connected to the mobile phone using App (Seek thermal) to allow temperature monitoring. Artificial Intelligence can play a vital role in the fight against COVID-19. AI is being successfully used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, diagnosis of COVID-19, disease management by resource allocation, facilitating training, record maintenance and pattern recognition for studying the disease trend. Therefore, AI is used as a type of alarm which be connected through Global Position System (GPS) to a central networking system to monitor the crowded areas of probable infections. In this case, the hospital in this neighborhood will be charged to let a mobile unit of assessment travel quickly to the infected people areas.

Artificial intelligence tools for pattern recognition

2017 ◽  
Author(s):  
Elena Acevedo ◽  
Antonio Acevedo ◽  
Federico Felipe ◽  
Pedro Avilés
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition

AN AUTO-PICKING STACKING VELOCITY ALGORITHM BASED ON AN AI AND PR APPROACH

1989 ◽  
Vol 03 (01) ◽  
pp. 103-111
Author(s):  
L. WU ◽  
Z. LUO ◽  
J. ZHOU ◽  
H. WANG
Keyword(s):  
Artificial Intelligence ◽  
Pattern Recognition ◽  
Data Processing ◽  
Seismic Data ◽  
Seismic Data Processing ◽  
Pattern Recognition Techniques ◽  
Automatic Algorithm

Stacking velocity is a very important parameter in seismic data processing. Until now the determination of stacking velocity has been done manually. This article proposes an automatic algorithm for picking stacking velocity. The algorithm uses artificial intelligence and pattern recognition techniques.

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