Deep Learning

2020 ◽  
pp. 124-141 ◽  
Author(s):  
Menaga D. ◽  
Revathi S.
Keyword(s):  
Information Retrieval ◽  
Deep Learning ◽  
Software Engineering ◽  
Multimedia Information ◽  
Research Area ◽  
Multimedia Application ◽  
Information Process ◽  
Display Devices ◽  
Storage Devices ◽  
Major Application

Multimedia application is a significant and growing research area because of the advances in technology of software engineering, storage devices, networks, and display devices. With the intention of satisfying multimedia information desires of users, it is essential to build an efficient multimedia information process, access, and analysis applications, which maintain various tasks, like retrieval, recommendation, search, classification, and clustering. Deep learning is an emerging technique in the sphere of multimedia information process, which solves both the crisis of conventional and recent researches. The main aim is to resolve the multimedia-related problems by the use of deep learning. The deep learning revolution is discussed with the depiction and feature. Finally, the major application also explained with respect to different fields. This chapter analyzes the crisis of retrieval after providing the successful discussion of multimedia information retrieval that is the ability of retrieving an object of every multimedia.

Semantic Multimedia Information Anaylsis for Retrieval Applications

2008 ◽  
pp. 880-897
Author(s):  
J. Magalhaes ◽  
Stefan Rüger
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Digital Libraries ◽  
Research Area ◽  
Multimedia Retrieval ◽  
Multimedia Content ◽  
Video Content ◽  
Comprehensive Review ◽  
Statistical Approaches ◽  
New Research

Most of the research in multimedia retrieval applications has focused on retrieval by content or retrieval by example. Since the classical review by Smeulders (2000) a new interest has grown immensely in the multimedia information retrieval community: retrieval by semantics. This exciting new research area arises as a combination of multimedia understanding, information extraction, information retrieval and digital libraries. This chapter presents a comprehensive review of analysis algorithms to extract semantic information from multimedia content. We discuss statistical approaches to analyse images and video content and conclude with a discussion regarding the described methods.

scholarly journals Semantic Multimedia Information Analysis for Retrieval Applications

2011 ◽  
pp. 47-65
Author(s):  
João Magalhães ◽  
Stefan Rüger
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Digital Libraries ◽  
Research Area ◽  
Multimedia Retrieval ◽  
Multimedia Content ◽  
Video Content ◽  
Comprehensive Review ◽  
Statistical Approaches ◽  
New Research

Most of the research in multimedia retrieval applications has focused on retrieval by content or retrieval by example. Since the classical review by Smeulders, Worring, Santini, Gupta, and Jain (2000), a new interest has grown immensely in the multimedia information retrieval community: retrieval by semantics. This exciting new research area arises as a combination of multimedia understanding, information extraction, information retrieval, and digital libraries. This chapter presents a comprehensive review of analysis algorithms in order to extract semantic information from multimedia content. We discuss statistical approaches to analyze images and video content and conclude with a discussion regarding the described methods.

Semantic Multimedia Information Anaylsis for Retrieval Applications

2011 ◽  
pp. 334-354 ◽  
Author(s):  
Joao Magalhaes ◽  
Stefan Ruger
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Digital Libraries ◽  
Research Area ◽  
Multimedia Retrieval ◽  
Multimedia Content ◽  
Video Content ◽  
Comprehensive Review ◽  
Statistical Approaches ◽  
New Research

Most of the research in multimedia retrieval applications has focused on retrieval by content or retrieval by example. Since the classical review by Smeulders (2000) a new interest has grown immensely in the multimedia information retrieval community: retrieval by semantics. This exciting new research area arises as a combination of multimedia understanding, information extraction, information retrieval and digital libraries. This chapter presents a comprehensive review of analysis algorithms to extract semantic information from multimedia content. We discuss statistical approaches to analyse images and video content and conclude with a discussion regarding the described methods.

Multimedia Information Retrieval at a Crossroad

2008 ◽  
pp. 242-249 ◽  
Author(s):  
Q. Li ◽  
J. Yang ◽  
Y. Zhuang
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Digital Libraries ◽  
High Speed ◽  
Web Applications ◽  
Multimedia Data ◽  
Multimedia Information Retrieval ◽  
Efficient Manner ◽  
Storage Devices ◽  
Digital World

In the late 1990s, the availability of powerful computing capability, large storage devices, high-speed networking and especially the advent of the Internet, led to a phenomenal growth of digital multimedia content in terms of size, diversity and impact. As suggested by its name, “multimedia” is a name given to a collection of multiple types of data, which include not only “traditional multimedia” such as images and videos, but also emerging media such as 3D graphics (like VRML objects) and Web animations (like Flash animations). Furthermore, multimedia techniques have been penetrating into a growing number of applications, ranging from document-editing software to digital libraries and many Web applications. For example, most people who have used Microsoft Word have tried to insert pictures and diagrams into their documents, and they have the experience of watching online video clips, such as movie trailers. In other words, multimedia data have been in every corner of the digital world. With the huge volume of multimedia data, finding and accessing the multimedia documents that satisfy people’s needs in an accurate and efficient manner became a non-trivial problem. This problem is defined as multimedia information retrieval.

scholarly journals Opportunities and Challenges in Code Search Tools

2022 ◽  
Vol 54 (9) ◽  
pp. 1-40
Author(s):  
Chao Liu ◽  
Xin Xia ◽  
David Lo ◽  
Cuiyun Gao ◽  
Xiaohu Yang ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Deep Learning ◽  
Software Engineering ◽  
Software Development ◽  
Large Scale ◽  
Research Trends ◽  
Publication Trends ◽  
Code Search ◽  
Search Tasks ◽  
Efficiency And Effectiveness

Code search is a core software engineering task. Effective code search tools can help developers substantially improve their software development efficiency and effectiveness. In recent years, many code search studies have leveraged different techniques, such as deep learning and information retrieval approaches, to retrieve expected code from a large-scale codebase. However, there is a lack of a comprehensive comparative summary of existing code search approaches. To understand the research trends in existing code search studies, we systematically reviewed 81 relevant studies. We investigated the publication trends of code search studies, analyzed key components, such as codebase, query, and modeling technique used to build code search tools, and classified existing tools into focusing on supporting seven different search tasks. Based on our findings, we identified a set of outstanding challenges in existing studies and a research roadmap for future code search research.

Multimedia Information Retrieval at a Crossroad

2011 ◽  
pp. 710-716
Author(s):  
Qing Li ◽  
Jun Yang ◽  
Yueting Zhuang
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Digital Libraries ◽  
High Speed ◽  
Web Applications ◽  
Multimedia Data ◽  
Multimedia Information Retrieval ◽  
Efficient Manner ◽  
Storage Devices ◽  
Digital World

In the late 1990s, the availability of powerful computing capability, large storage devices, high-speed networking and especially the advent of the Internet, led to a phenomenal growth of digital multimedia content in terms of size, diversity and impact. As suggested by its name, “multimedia” is a name given to a collection of multiple types of data, which include not only “traditional multimedia” such as images and videos, but also emerging media such as 3D graphics (like VRML objects) and Web animations (like Flash animations). Furthermore, multimedia techniques have been penetrating into a growing number of applications, ranging from document-editing software to digital libraries and many Web applications. For example, most people who have used Microsoft Word have tried to insert pictures and diagrams into their documents, and they have the experience of watching online video clips, such as movie trailers. In other words, multimedia data have been in every corner of the digital world. With the huge volume of multimedia data, finding and accessing the multimedia documents that satisfy people’s needs in an accurate and efficient manner became a non-trivial problem. This problem is defined as multimedia information retrieval.

Deep Learning Based High-Resolution Remote Sensing Image classification

2017 ◽  
Vol 7 (10) ◽  
pp. 22
Author(s):  
Sumit Kaur
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Deep Learning ◽  
Image Classification ◽  
Language Processing ◽  
Object Perception ◽  
Remote Sensing Image ◽  
Research Area ◽  
Remote Sensing Image Classification ◽  
Unsupervised Algorithms

Abstract- Deep learning is an emerging research area in machine learning and pattern recognition field which has been presented with the goal of drawing Machine Learning nearer to one of its unique objectives, Artificial Intelligence. It tries to mimic the human brain, which is capable of processing and learning from the complex input data and solving different kinds of complicated tasks well. Deep learning (DL) basically based on a set of supervised and unsupervised algorithms that attempt to model higher level abstractions in data and make it self-learning for hierarchical representation for classification. In the recent years, it has attracted much attention due to its state-of-the-art performance in diverse areas like object perception, speech recognition, computer vision, collaborative filtering and natural language processing. This paper will present a survey on different deep learning techniques for remote sensing image classification. 

scholarly journals Global and Latin American female participation in evidence-based software engineering: a systematic mapping study

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Katia Romero Felizardo ◽  
Amanda Möhring Ramos ◽  
Claudia de O. Melo ◽  
Érica Ferreira de Souza ◽  
Nandamudi L. Vijaykumar ◽  
...  
Keyword(s):  
Software Engineering ◽  
Latin American ◽  
Gender Issue ◽  
Research Area ◽  
Systematic Mapping Study ◽  
Evidence Based ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Participation Of Women ◽  
New Generation

Abstract Context While the digital economy requires a new generation of technology for scientists and practitioners, the software engineering (SE) field faces a gender crisis. SE research is a global enterprise that requires the participation of both genders for the advancement of science and evidence-based practice. However, women across the world tend to be significantly underrepresented in such research, receiving less funding and less participation, frequently, than men as authors in research publications. Data about this phenomenon is still sparse and incomplete; particularly in evidence-based software engineering (EBSE), there are no studies that analyze the participation of women in this research area. Objective The objective of this work is to present the results of a systematic mapping study (SM) conducted to collect and evaluate evidence on female researchers who have contributed to the area of EBSE. Method Our SM was performed by manually searching studies in the major conferences and journals of EBSE. We identified 981 studies and 183 were authored/co-authored by women and, therefore, included. Results Contributions from women in secondary studies have globally increased over the years, but it is still concentrated in European countries. Additionally, collaboration among research groups is still fragile, based on a few women as a bridge. Latin American researchers contribute a great deal to the field, despite they do not collaborate as much within their region. Conclusions The findings from this study are expected to be aggregated to the existing knowledge with respect to women’s contribution to the EBSE area. We expect that our results bring up a reflection on the gender issue and motivate actions and policies to attract female researchers to this area.

Open System for Indexing and Retrieving Multimedia Information

2013 ◽  
Author(s):  
Hanene Maghrebi ◽  
Amos David
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Open System ◽  
Large Volume ◽  
Retrieval System ◽  
Main Idea ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Multimedia Content ◽  
Nous Proposons

Managing the increasing growth of multimedia content still poses some problems. The challenge is to propose relevant information to the users among the large volume of information available. The main idea that drives our approach is to provide an open information retrieval system, which can adapt its results to several…La gestion de l’information multimédia soulève encore quelques problèmes. Le défi est de pouvoir proposer à l’utilisateur des informations pertinentes parmi la quantité d’information qui ne cesse de s’accroître. Dans cette lignée, nous proposons un système ouvert de recherche d’information capable d’adapter ses résultats aux différents… 

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