Multiple-model adaptive estimators: Open problems and future directions

2007 ◽  
Author(s):  
A. Pedro Aguiar
Keyword(s):  
Multiple Model ◽  
Open Problems ◽  
Future Directions ◽  
Adaptive Estimators

Pose Tracking in Augmented Reality of Cultural Heritage

2017 ◽  
Vol 1 (1) ◽  
pp. 123-131
Author(s):  
Daniel Asmar
Keyword(s):  
Augmented Reality ◽  
Cultural Heritage ◽  
Paper Briefly ◽  
Open Problems ◽  
Future Directions ◽  
Advantages And Disadvantages ◽  
Pose Tracking ◽  
Solution Methods

This paper briefly surveys pose tracking methods used for augmented reality applications in cultural heritage. The paper primarily benefits scholars and practitioners in the areas of electronic heritage. Pose tracking techniques are categorized as either being dependent or independent of their surrounding; accordingly, various solution methods in the literature are presented along with their advantages and disadvantages. I conclude the paper with a discussion on the open problems in pose tracking in cultural heritage and recommend future directions of research in this field.

Index, sub-index and sub-factor of groups with interactions to number theory

2019 ◽  
Vol 19 (06) ◽  
pp. 2050101
Author(s):  
M. H. Hooshmand
Keyword(s):  
Number Theory ◽  
Direct Product ◽  
Prime Numbers ◽  
Additive Number Theory ◽  
Open Problems ◽  
Famous Conjecture ◽  
Future Directions ◽  
Left And Right ◽  
The Difference ◽  
Equivalent Conditions

This paper is the first step of a new topic about groups which has close relations and applications to number theory. Considering the factorization of a group into a direct product of two subsets, and since every subgroup is a left and right factor, we observed that the index conception can be generalized for a class of factors. But, thereafter, we found that every subset [Formula: see text] of a group [Formula: see text] has four related sub-indexes: right, left, upper and lower sub-indexes [Formula: see text], [Formula: see text] which agree with the conception index of subgroups, and all of them are equal if [Formula: see text] is a subgroup or normal sub-semigroup of [Formula: see text]. As a result of the topic, we introduce some equivalent conditions to a famous conjecture for prime numbers (“every even number is the difference of two primes”) that one of them is: the prime numbers set is index stable (i.e. all of its sub-indexes are equal) in integers and [Formula: see text]. Index stable groups (i.e. those whose subsets are all index stable) are a challenging subject of the topic with several results and ideas. Regarding the extension of the theory, we give some methods for evaluation of sub-indexes, by using the left and right differences of subsets. At last, we pose many open problems, questions, a proposal for additive number theory, and show some future directions of researches and projects for the theory.

Identification and Convergence Analysis of a Class of Continuous-Time Multiple-Model Adaptive Estimators

2008 ◽  
Vol 41 (2) ◽  
pp. 8605-8610 ◽  
Author(s):  
A. Pedro Aguiar ◽  
Vahid Hassani ◽  
António M. Pascoal ◽  
Michael Athans
Keyword(s):  
Convergence Analysis ◽  
Continuous Time ◽  
Multiple Model ◽  
Adaptive Estimators

scholarly journals A comprehensive review of deep learning-based single image super-resolution

2021 ◽  
Vol 7 ◽  
pp. e621
Author(s):  
Syed Muhammad Arsalan Bashir ◽  
Yi Wang ◽  
Mahrukh Khan ◽  
Yilong Niu
Keyword(s):  
Deep Learning ◽  
Super Resolution ◽  
Single Image ◽  
Open Problems ◽  
Future Directions ◽  
Attention Network ◽  
Domain Specific ◽  
Feedback Network ◽  
Image Super Resolution ◽  
Single Image Super Resolution

Image super-resolution (SR) is one of the vital image processing methods that improve the resolution of an image in the field of computer vision. In the last two decades, significant progress has been made in the field of super-resolution, especially by utilizing deep learning methods. This survey is an effort to provide a detailed survey of recent progress in single-image super-resolution in the perspective of deep learning while also informing about the initial classical methods used for image super-resolution. The survey classifies the image SR methods into four categories, i.e., classical methods, supervised learning-based methods, unsupervised learning-based methods, and domain-specific SR methods. We also introduce the problem of SR to provide intuition about image quality metrics, available reference datasets, and SR challenges. Deep learning-based approaches of SR are evaluated using a reference dataset. Some of the reviewed state-of-the-art image SR methods include the enhanced deep SR network (EDSR), cycle-in-cycle GAN (CinCGAN), multiscale residual network (MSRN), meta residual dense network (Meta-RDN), recurrent back-projection network (RBPN), second-order attention network (SAN), SR feedback network (SRFBN) and the wavelet-based residual attention network (WRAN). Finally, this survey is concluded with future directions and trends in SR and open problems in SR to be addressed by the researchers.

Hard Clues in Soft Environments

2016 ◽  
pp. 112-138
Author(s):  
Andrea Atzeni ◽  
Paolo Smiraglia ◽  
Andrea Siringo
Keyword(s):  
Digital Forensics ◽  
Cloud Environment ◽  
Open Problems ◽  
Future Directions ◽  
Cloud Technology ◽  
Cloud Forensics ◽  
Security Issues

Cloud forensics is an open and important area of research due to the growing interest in cloud technology. The increasing frequency of digital investigations brings with it the need for studying specific scenarios in the area of forensics, both when evidence are inside the cloud and when the cloud can be used as platform to perform the investigations. In this chapter we highlight the problems digital forensics must deal with in the Cloud. We introduce historical roots of digital forensics, as well as an overall background about the Cloud and we provide possible meanings of cloud forensics, based on available definitions. Since the cloud introduces different architectural paradigm that affects all the phases of a forensics investigation, in this survey we detail many security issues digital forensics have to face in a cloud environment. We describe when and what available solutions exist and, on the contrary, the still open problems, and we discuss possible future directions in this field.

scholarly journals Anomaly Mining - Past, Present and Future

2021 ◽  
Author(s):  
Leman Akoglu
Keyword(s):  
Real World ◽  
Point Cloud ◽  
Personal View ◽  
Open Problems ◽  
Future Directions ◽  
Main Research ◽  
Research Problems ◽  
Space Limit ◽  
Recent Trends ◽  
Technical Details

Anomaly mining is an important problem that finds numerous applications in various real world do- mains such as environmental monitoring, cybersecurity, finance, healthcare and medicine, to name a few. In this article, I focus on two areas, (1) point-cloud and (2) graph-based anomaly mining. I aim to present a broad view of each area, and discuss classes of main research problems, recent trends and future directions. I conclude with key take-aways and overarching open problems. Disclaimer. I try to provide an overview of past and recent trends in both areas within 4 pages. Undoubtedly, these are my personal view of the trends, which can be organized differently. For brevity, I omit all technical details and refer to corresponding papers. Again, due to space limit, it is not possible to include all (even most relevant) references, but a few representative examples.

A Review of Non-Minutiae Based Fingerprint Features

2018 ◽  
Vol 8 (1) ◽  
pp. 32-58 ◽  
Author(s):  
Ravinder Kumar
Keyword(s):  
Machine Learning ◽  
Critical Review ◽  
State Of The Art ◽  
The State ◽  
Fingerprint Matching ◽  
Open Problems ◽  
Future Directions ◽  
Detailed Review ◽  
The Future

This article presents a critical review of extensive research on automatic fingerprint matching over a decade. In particular, the focus is made on the non-minutiae-based features and machine-learning-based fingerprint matching approaches. This article highlights the problems pertaining to the minutiae-based features and presents a detailed review on the state-of-the-art of non-minutiae-based features. This article also presents an overview of the state-of-the-art fingerprint benchmark databases, along with the open problems and the future directions for the fingerprint matching.

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