An Ensemble Feature Selection Framework of Sonar Targets Using Symmetrical Uncertainty and Multi-Layer Perceptron (SU-MLP)

Potharaju, Sai Prasad; Sreedevi, M.; Amiripalli, Shanmuk Srinivas

doi:10.1007/978-981-13-0617-4_24

Cited by 16 publications

(14 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In some data analysis cases such as classification or regression can be done in the reduced space more exactly than the original data space. In measurements of Machine Learning, include see the different problems [16] , in few cases, dataanalysis such as data regression or data classification can be done in the reduced space more accurately than in the original space.…”

Section: Feature Selectionmentioning

confidence: 99%

Cluster Optimization for Boundary Points using Distributive Progressive Feature Selection Algorithm

Ramesh¹

2021

TURCOMAT

View full text Add to dashboard Cite

A group of different data objects is classified as similar objects is known as clusters. It is the process of finding homogeneous data items like patterns, documents etc. and then group the homogenous data items togetherothers groupsmay have dissimilar data items. Most of the clustering methods are either crisp or fuzzy and moreover member allocation to the respective clusters is strictly based on similarity measures and membership functions.Both of the methods have limitations in terms of membership. One strictly decides a sample must belong to single cluster and other anyway fuzzy i.e probability. Finally, Quality and Purity like measure are applied to understand how well clusters are created. But there is a grey area in between i.e. ‘Boundary Points’ and ‘Moderately Far’ points from the cluster centre. We considered the cluster quality [18], processing time and relevant features identification as basis for our problem statement and implemented Zone based clustering by using map reducer concept. I have implemented the process to find far points from different clusters and generate a new cluster, repeat the above process until cluster quantity is stabilized. By using this processwe can improve the cluster quality and processing time also.

show abstract

Section: Feature Selectionmentioning

confidence: 99%

Cluster Optimization for Boundary Points using Distributive Progressive Feature Selection Algorithm

Ramesh¹

2021

TURCOMAT

View full text Add to dashboard Cite

show abstract

“…Both feature level and also the decision level integration were implemented. According to that paper the feature selection's [19] quality will determine the accuracy of the recognition directly, whereas the feature selection wants some more professional knowledge and also the recognition rate takes more time, and is low also laborious. The result proved that performance of both the systems was similar.…”

Section: Literature Reviewmentioning

confidence: 99%

An Efficient and Accurate Real Time Facial Expression Detection Using CNN

Srujana¹,

Devi²

2021

pae

View full text Add to dashboard Cite

Real Facial expression acknowledgment (RTFER) has become a functioning examination zone that finds a ton of utilizations in territories like human-PC interfaces, human feeling investigation, mental investigation, clinical conclusion and so on Mainstream strategies utilized for this intention depend on math and appearance. Profound convolutional neural networks (CNN) have appeared to beat customary strategies in different visual acknowledgment errands including Facial Expression Recognition. Despite the fact that endeavours are made to improve the exactness of RTFER frameworks utilizing CNN, for functional applications existing strategies probably won't be adequate. This examination incorporates a conventional audit of RTFER frameworks utilizing CNN and their qualities and restrictions which assist us with comprehension and improve the RTFER frameworks further.

show abstract

“…A great deal of work has been done in the advancement of blockchain, but the amount of investigation remains limited. in order to thoroughly research block chain's current academic research, it incorporates the topics of business and economics [24]. (Junyao Wang et.al, 2019) focused on Blockchain development and application are being explored in both academic and commercial environments.…”

Section: Literature Reviewmentioning

confidence: 99%

A Systematic Review of Blockchain Technology and Its Applications

Naikwadi

Kharade

Yuvaraj

et al. 2021

Recent Trends in Intensive Computing

View full text Add to dashboard Cite

Blockchain technology could radically transform our business environment in the decades to come. It has the power to redefine our views of business processes and may even impact our overall economy. The works comprehensively document the implementation of blockchain applications in various sectors. Our goal is to determine what state blockchain technology is in and what kinds of applications it has. A large majority of the current blockchain-related research is dedicated to crypto currencies, such as Bitcoin. Only a small percentage of work is dedicated to exploring the wide range of potential blockchain technology applications. Blockchain technology has multiple applications across multiple industries. This study attempts to determine the opportunities and threats presented by Blockchain Technology for current or future applications. The number of published studies that were studied carefully and critically and added to the Block chain’s body of knowledge was large.

show abstract

An Ensemble Feature Selection Framework of Sonar Targets Using Symmetrical Uncertainty and Multi-Layer Perceptron (SU-MLP)

Cited by 16 publications

References 13 publications

Cluster Optimization for Boundary Points using Distributive Progressive Feature Selection Algorithm

Cluster Optimization for Boundary Points using Distributive Progressive Feature Selection Algorithm

An Efficient and Accurate Real Time Facial Expression Detection Using CNN

A Systematic Review of Blockchain Technology and Its Applications

Contact Info

Product

Resources

About