Facial Expression Recognition Using Fusion of Deep Learning and Multiple Features

Srinivas, M.B.; Saurav, Sanjeev; Nayak, Akshay; P, Murukessan A

doi:10.1002/9781119769262.ch13

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…In the field of machine learning, the binary classification problem is a central one used to build up models and explain many types of phenomena ( Srinivas, Sucharitha & Matta, 2021 ; Zaki & Meira, 2020 ). Most classical binary classification approaches ultimately provide a rule for assigning label probabilities to data instances based on the information provided by some training data.…”

Section: Related Workmentioning

confidence: 99%

A game-theoretic model for the classification of selected oil companies’ price changes

Lung¹,

Duma²

2023

PeerJ Computer Science

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One of the essential properties of a machine learning model is to be able to capture nuanced connections within data. This ability can be enhanced by considering alternative solution concepts, such as those offered by game theory. In this article, the Nash equilibrium is used as a solution concept to estimate probit parameters for the binary classification problem. A non-cooperative game is proposed in which data variables are players that attempt to maximize their marginal contribution to the log-likelihood function. A differential evolution algorithm is adapted to solve the proposed game. The new method is used to study the price changes of the Romanian oil company, OMV Petrom SA Romania, relative to the price of oil (crude and Brent) and the evolution of two other major oil companies with influence in the region. Results show that the proposed method outperforms the baseline probit and classical classification approaches in predicting price changes.

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Section: Related Workmentioning

confidence: 99%

A game-theoretic model for the classification of selected oil companies’ price changes

Lung¹,

Duma²

2023

PeerJ Computer Science

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“…Therefore, linear search, the well-known method for stationary scanning techniques, was chosen. However, there are several machine learning methods, both supervised and unsupervised [9,10], that can be applied to skimming techniques. Supervised learning relies on labeled data and uses other data as input to build the model.…”

Section: Introductionmentioning

confidence: 99%

JASPER: Journal Article Selection Program for Non-native English Readers

Keandoungchun,

Angskun,

Angskun

2024

JAIT

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Typically, reading a journal article can be timeconsuming, mainly for non-native English readers, because academic writing usually uses complicated vocabulary and sentences. Therefore, this paper proposes a Journal Article Selection Program for Non-native English Readers (JASPER) for selecting journal articles from abstracts using scanning and skimming techniques. JASPER employs linear searching as a scanning technique and a novel multi-layer Latent Dirichlet Allocation (LDA) as a skimming technique. It automatically classifies journal articles into multi-layer topics and selects only articles with related topics to reduce the number of articles readers must read. JASPER is evaluated in terms of accuracy and efficiency using journal articles on Computer Science topics. It achieved an average of 82.62% of the F-measure. It can also reduce the number of journal articles by an average of 98.68%. Therefore, JASPER can practically reduce the number of journal articles for non-native English readers.

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Investigating Dense Cnn Architectures: A Case Study of Facial Emotional Recognition Systems

Kyei,

Appiahene,

Ayidzoe

et al. 2024

Preprint

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Facial Expression Recognition Using Fusion of Deep Learning and Multiple Features

Cited by 3 publications

References 17 publications

A game-theoretic model for the classification of selected oil companies’ price changes

A game-theoretic model for the classification of selected oil companies’ price changes

JASPER: Journal Article Selection Program for Non-native English Readers

Investigating Dense Cnn Architectures: A Case Study of Facial Emotional Recognition Systems

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