Recent advances and emerging challenges of feature selection in the context of big data
V Bolón-Canedo, N Sánchez-Maroño… - Knowledge-based …, 2015 - Elsevier
In an era of growing data complexity and volume and the advent of big data, feature
selection has a key role to play in helping reduce high-dimensionality in machine learning …
selection has a key role to play in helping reduce high-dimensionality in machine learning …
[HTML][HTML] Application of deep learning and machine learning models to detect COVID-19 face masks-A review
E Mbunge, S Simelane, SG Fashoto… - Sustainable Operations …, 2021 - Elsevier
The continuous COVID-19 upsurge and emerging variants present unprecedented
challenges in many health systems. Many regulatory authorities have instituted the …
challenges in many health systems. Many regulatory authorities have instituted the …
A survey on evolutionary computation approaches to feature selection
Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …
dimensionality of the data and increase the performance of an algorithm, such as a …
Opposition chaotic fitness mutation based adaptive inertia weight BPSO for feature selection in text clustering
Due to the ever increasing number of documents in the digital form, automated text
clustering has become a promising method for the text analysis in last few decades. A major …
clustering has become a promising method for the text analysis in last few decades. A major …
A survey of 2D face recognition techniques
M Chihaoui, A Elkefi, W Bellil, C Ben Amar - Computers, 2016 - mdpi.com
Despite the existence of various biometric techniques, like fingerprints, iris scan, as well as
hand geometry, the most efficient and more widely-used one is face recognition. This is …
hand geometry, the most efficient and more widely-used one is face recognition. This is …
[图书][B] Encyclopedia of information science and technology
DBA Khosrow-Pour - 2005 - books.google.com
Technology is constantly changing; what is cutting edge today is obsolete tomorrow. In this
ever-evolving environment, educators, researchers and professionals of the discipline need …
ever-evolving environment, educators, researchers and professionals of the discipline need …
A comprehensive survey on the process, methods, evaluation, and challenges of feature selection
Feature selection is employed to reduce the feature dimensions and computational
complexity by eliminating irrelevant and redundant features. A vast amount of increasing …
complexity by eliminating irrelevant and redundant features. A vast amount of increasing …
Content-based image retrieval using PSO and k-means clustering algorithm
In various application domains such as website, education, crime prevention, commerce,
and biomedicine, the volume of digital data is increasing rapidly. The trouble appears when …
and biomedicine, the volume of digital data is increasing rapidly. The trouble appears when …
Face recognition using transform domain feature extraction and PSO-based feature selection
NLA Krisshna, VK Deepak, K Manikantan… - Applied Soft …, 2014 - Elsevier
This paper presents two new techniques, viz., DWT Dual-subband Frequency-domain
Feature Extraction (DDFFE) and Threshold-Based Binary Particle Swarm Optimization …
Feature Extraction (DDFFE) and Threshold-Based Binary Particle Swarm Optimization …
Facial expression recognition of online learners from real-time videos using a novel deep learning model
M Jagadeesh, B Baranidharan - Multimedia Systems, 2022 - Springer
In every learning setting, in classrooms or online, a student's emotions throughout course
involvement play a critical role. It employs disturbing, excite, and eye and head movement …
involvement play a critical role. It employs disturbing, excite, and eye and head movement …