Noise Removal Based Query Pre-processing to Improve Face Search Performance in Large Scale Video Databases

2019 ◽  
Author(s):  
Hung-Quoc Vo ◽  
Vu-Minh-Hieu Dang ◽  
Vinh-Tiep Nguyen ◽  
Duy-Dinh Le
Keyword(s):  
Large Scale ◽  
Noise Removal ◽  
Search Performance ◽  
Video Databases ◽  
Face Search

scholarly journals Large-Scale Complex Network Community Detection Combined with Local Search and Genetic Algorithm

2020 ◽  
Vol 10 (9) ◽  
pp. 3126
Author(s):  
Desheng Lyu ◽  
Bei Wang ◽  
Weizhe Zhang
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Community Structure ◽  
Local Search ◽  
Complex Networks ◽  
Community Detection ◽  
Large Scale ◽  
Particle Swarm ◽  
Search Performance ◽  
Swarm Optimization

With the development of network technology and the continuous advancement of society, the combination of various industries and the Internet has produced many large-scale complex networks. A common feature of complex networks is the community structure, which divides the network into clusters with tight internal connections and loose external connections. The community structure reveals the important structure and topological characteristics of the network. The detection of the community structure plays an important role in social network analysis and information recommendation. Therefore, based on the relevant theory of complex networks, this paper introduces several common community detection algorithms, analyzes the principles of particle swarm optimization (PSO) and genetic algorithm and proposes a particle swarm-genetic algorithm based on the hybrid algorithm strategy. According to the test function, the single and the proposed algorithm are tested, respectively. The results show that the algorithm can maintain the good local search performance of the particle swarm optimization algorithm and also utilizes the good global search ability of the genetic algorithm (GA) and has good algorithm performance. Experiments on each community detection algorithm on real network and artificially generated network data sets show that the particle swarm-genetic algorithm has better efficiency in large-scale complex real networks or artificially generated networks.

scholarly journals Diffuse retro-reflective imaging for improved video tracking of mosquitoes at human baited bednets

2020 ◽  
Vol 7 (5) ◽  
pp. 191951 ◽  
Author(s):  
Vitaly Voloshin ◽  
Christian Kröner ◽  
Chandrabhan Seniya ◽  
Gregory P. D. Murray ◽  
Amy Guy ◽  
...  
Keyword(s):  
Large Scale ◽  
Imaging Techniques ◽  
Field Studies ◽  
Noise Removal ◽  
Optical Signal ◽  
Video Tracking ◽  
Ease Of Use ◽  
Model Systems ◽  
Mosquito Behaviour ◽  
Set Up

Robust imaging techniques for tracking insects have been essential tools in numerous laboratory and field studies on pests, beneficial insects and model systems. Recent innovations in optical imaging systems and associated signal processing have enabled detailed characterization of nocturnal mosquito behaviour around bednets and improvements in bednet design, a global essential for protecting populations against malaria. Nonetheless, there remain challenges around ease of use for large-scale in situ recordings and extracting data reliably in the critical areas of the bednet where the optical signal is attenuated. Here, we introduce a retro-reflective screen at the back of the measurement volume, which can simultaneously provide diffuse illumination, and remove optical alignment issues while requiring only one-sided access to the measurement space. The illumination becomes significantly more uniform, although noise removal algorithms are needed to reduce the effects of shot noise, particularly across low-intensity bednet regions. By systematically introducing mosquitoes in front of and behind the bednet in laboratory experiments, we are able to demonstrate robust tracking in these challenging areas. Overall, the retro-reflective imaging set-up delivers mosquito segmentation rates in excess of 90% compared to less than 70% with backlit systems.

scholarly journals Diffuse retro-reflective imaging for improved video tracking of mosquitoes at human baited bednets

2019 ◽  
Author(s):  
Vitaly Voloshin ◽  
Christian Kröner ◽  
Chandrabhan Seniya ◽  
Gregory P. D. Murray ◽  
Amy Guy ◽  
...  
Keyword(s):  
Large Scale ◽  
Imaging Techniques ◽  
Field Studies ◽  
Noise Removal ◽  
Optical Signal ◽  
Video Tracking ◽  
Ease Of Use ◽  
Model Systems ◽  
Diffuse Illumination ◽  
Mosquito Behaviour

AbstractRobust imaging techniques for tracking insects have been essential tools in numerous laboratory and field studies on pests, beneficial insects and model systems. Recent innovations in optical imaging systems and associated signal processing have enabled detailed characterisation of nocturnal mosquito behaviour around bednets and improvements in bednet design, a global essential for protecting populations against malaria. Nonetheless, there remain challenges around ease of use for large scale in situ recordings and extracting data reliably in the critical areas of the bednet where the optical signal is attenuated. Here we introduce a retro-reflective screen at the back of the measurement volume, which can simultaneously provide diffuse illumination, and remove optical alignment issues whilst requiring only one-sided access to the measurement space. The illumination becomes significantly more uniform, although, noise removal algorithms are needed to reduce the effects of shot noise particularly across low intensity bednet regions. By systematically introducing mosquitoes in front and behind the bednet in lab experiments we are able to demonstrate robust tracking in these challenging areas. Overall, the retro-reflective imaging setup delivers mosquito segmentation rates in excess of 90% compared to less than 70% with back-lit systems.

Decentralized Search and the Clustering Paradox in Large Scale Information Networks

2012 ◽  
pp. 29-46
Author(s):  
Weimao Ke
Keyword(s):  
Information Retrieval ◽  
Large Scale ◽  
Information Networks ◽  
Search Performance ◽  
Retrieval Models ◽  
Information Spaces ◽  
Decentralized Search ◽  
Key Issues ◽  
Large Scale Networks ◽  
The Impact

Amid the rapid growth of information today is the increasing challenge for people to navigate its magnitude. Dynamics and heterogeneity of large information spaces such as the Web raise important questions about information retrieval in these environments. Collection of all information in advance and centralization of IR operations are extremely difficult, if not impossible, because systems are dynamic and information is distributed. The chapter discusses some of the key issues facing classic information retrieval models and presents a decentralized, organic view of information systems pertaining to search in large scale networks. It focuses on the impact of network structure on search performance and discusses a phenomenon we refer to as the Clustering Paradox, in which the topology of interconnected systems imposes a scalability limit.

Revisiting FPGA Implementation of Digital Filters and Exploring Approximate Computing on Biomedical Signals

2020 ◽  
Vol 10 (9) ◽  
pp. 2000-2004
Author(s):  
Wang Hui ◽  
Gong Chang ◽  
S. Saravanan ◽  
V. Gomathi ◽  
R. Valarmathi ◽  
...  
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Noise Removal ◽  
Multimedia Data ◽  
Digital Data ◽  
Functional Verification ◽  
Approximate Computing ◽  
Human Beings ◽  
Volume Data ◽  
Simulation Results

In recent years, the approximate computing becomes popular in the era of VLSI (very large scale integration) domain to arrive better power, area, and delay outcomes at the cost of lower precision loss. Also, the human beings are not so intelligent to see/observe/listen the processed digital data; means even if some of the data loss occurs human beings are unable to notice them. This behavior set the engineers to research on approximate computing which are very useful in the multimedia data processing, data communications, high-volume data storage, etc. In this study, the experiments such as hum-noise removal, filters on QRS detection are implemented on an Altera FPGA EP4CEF29C7 device using Quartus II 13.1 synthesis software tool and the simulation results on device utilization reports, the speed and the power are obtained. Simulation results reveal that the approximate computational filters offer better power, area, and speed results than the conventional ones. Also, Matlab 9.4 (R2018a) simulation was used to carry out the functional verification of the actual and approximate filters.

Fast face sequence matching in large-scale video databases

2011 ◽  
Author(s):  
Hung Thanh Vu ◽  
Thanh Duc Ngo ◽  
Thao Ngoc Nguyen ◽  
Duy-Dinh Le ◽  
Shin'ichi Satoh ◽  
...  
Keyword(s):  
Large Scale ◽  
Sequence Matching ◽  
Video Databases

Efficient indexing and retrieval of large-scale geo-tagged video databases

2016 ◽  
Vol 20 (4) ◽  
pp. 829-857 ◽  
Author(s):  
Ying Lu ◽  
Cyrus Shahabi ◽  
Seon Ho Kim
Keyword(s):  
Large Scale ◽  
Video Databases ◽  
Indexing And Retrieval

scholarly journals A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Yuqi Fan ◽  
Junpeng Shao ◽  
Guitao Sun ◽  
Xuan Shao
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Iteration Process ◽  
Function Optimization ◽  
Search Performance ◽  
Global Function ◽  
Salp Swarm Algorithm ◽  
Search Speed ◽  
Swarm Algorithm ◽  
Feasible Solutions

Metaheuristic algorithms are often applied to global function optimization problems. To overcome the poor real-time performance and low precision of the basic salp swarm algorithm, this paper introduces a novel hybrid algorithm inspired by the perturbation weight mechanism. The proposed perturbation weight salp swarm algorithm has the advantages of a broad search scope and a strong balance between exploration and exploitation and retains a relatively low computational complexity when dealing with numerous large-scale problems. A new coefficient factor is introduced to the basic salp swarm algorithm, and new update strategies for the leader position and the followers are introduced in the search phase. The new leader position updating strategy has a specific bounded scope and strong search performance, thus accelerating the iteration process. The new follower updating strategy maintains the diversity of feasible solutions while reducing the computational load. This paper describes the application of the proposed algorithm to low-dimension and variable-dimension functions. This paper also presents iteration curves, box-plot charts, and search-path graphics to verify the accuracy of the proposed algorithm. The experimental results demonstrate that the perturbation weight salp swarm algorithm offers a better search speed and search balance than the basic salp swarm algorithm in different environments.

scholarly journals Supporting Book Search: A Comprehensive Comparison of Tags vs. Controlled Vocabulary Metadata

2017 ◽  
Vol 1 (1) ◽  
pp. 17-34 ◽  
Author(s):  
Toine Bogers ◽  
Vivien Petras
Keyword(s):  
Information Needs ◽  
Large Scale ◽  
Controlled Vocabulary ◽  
Test Collection ◽  
Search Performance ◽  
Empirical Comparison ◽  
Controlled Vocabularies ◽  
Complex Information ◽  
Depth Analysis ◽  
Comprehensive Comparison

Abstract Book search is far from a solved problem. Complex information needs often go beyond bibliographic facts and cover a combination of different aspects, such as specific genres or plot elements, engagement or novelty. Conventional book metadata may not be sufficient to address these kinds of information needs. In this paper, we present a large-scale empirical comparison of the effectiveness of book metadata elements for searching complex information needs. Using a test collection of over 2 million book records and over 330 real-world book search requests, we perform a highly controlled and in-depth analysis of topical metadata, comparing controlled vocabularies with social tags. Tags perform better overall in this setting, but controlled vocabulary terms provide complementary information, which will improve a search. We analyze potential underlying factors that contribute to search performance, such as the relevance aspect(s) mentioned in a request or the type of book. In addition, we investigate the possible causes of search failure. We conclude that neither tags nor controlled vocabularies are wholly suited to handling the complex information needs in book search, which means that different approaches to describe topical information in books are needed.

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