Auditory Attention State Decoding for the Quiet and Hypothetical Environment: A Comparison Between bLSTM and SVM

Nasrin, Fatema; Ahmed, Nafiz Ishtiaque; Rahman, Muhammad Arifur

doi:10.1007/978-981-33-4673-4_23

Cited by 19 publications

(3 citation statements)

References 25 publications

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“…There is a vast array of works of machine learning in diverse area i.e. Classification of Fake News [4], Facial Spoof Detection [5], Image classification [6], Auditory attention state [7], Computational biology [8], Trust management for IOT [9], Text processing [10,11] are going.…”

Section: Literature Reviewmentioning

confidence: 99%

A Recommender System for Adaptive Examination Preparation using Pearson Correlation Collaborative Filtering

Hossain,

Tasnim,

Hoque

et al. 2021

Int J Auto AI Mach learn

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Distance learning is any type of far-off instruction where the understudy isn't actually present for the exercise. It is blasting gratitude to the force of the Internet. Distance learning plays a vital role for examination preparation where multiple choice questions can be utilized to evaluate the performance of students. Multiple Choice Question (MCQ) is a type of question used in the examination to evaluate the performance of students accordingly where usually four options are given along with the question, and one has to choose the correct answer. This research includes a simulation model that has been built to keep the learners continue to learn the subjects they might be weak in. We have developed a methodology that may guide a student to update his/her area of weakness by using a recommender system based on Pearson Correlation Collaborative Filtering approach. The paper describes a recommender system that will keep track of a learner's profile and create an adaptive training mechanism using the performance matrix.

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Section: Literature Reviewmentioning

confidence: 99%

A Recommender System for Adaptive Examination Preparation using Pearson Correlation Collaborative Filtering

Hossain,

Tasnim,

Hoque

et al. 2021

Int J Auto AI Mach learn

View full text Add to dashboard Cite

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“…One could consider the three imputation categories outlined by Zhang [2] as an optimization problem. The bio-inspired algorithms were extensively tested in the iterative imputation category for their balance of accuracy, development time and computing power.It is important to note that the majority of approaches to imputation of missing values involve bioinspired algorithms, machine learning algorithms for healthcare [3,4], ontology datasets for language processing [5], wireless communications [6], cognitive eye tracking systems [7].Although these algorithms are usually used to increase the intersection or to help with parameter adjustment instead of predicting the data themselves [8,9].…”

Section: Introductionmentioning

confidence: 99%

Transfer Learning Approach Applied to Data Imputation

Sultana¹

2022

Preprint

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The challenge of bearing fault diagnosis is great due to the large amount of data that needs to beanalysed. The goal of this analysis is to propose a good fit approach to dealing with faulty data inorder to optimize the correctness of data. A transfer learning method can be used to achieve this.Our study suggests that the transfer learning performs significantly better than other methods whenit comes to overcoming faulty bearing data. The transfer learning algorithm is accurate up to 90%of the time when trying to correct for this type of error.

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“…It might be challenging for those who lose their vision early to operate in society. This product's use might be detrimental to speech [1], language [2], and cognitive development [3,4] and machine learning [5]. For visual loss to be overcome, early detection is crucial.…”

Section: Introductionmentioning

confidence: 99%

The Ability to Detect Vision Loss from the Visual Cortex Using iEEG is a Key Advance in the Treatment of The Condition

Lee¹

2022

Preprint

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Individuals with early vision impairment often have difficulty navigating in the world. If you want to overcome your early vision misfortune, it's important to be distinct in your vision goals. This research can focus on recognizing vision misfortune early using EEG signals and light-sensitive receptors. The human vision method is difficult and troublesome to induce.The vision cortex is the part of the brain that plays an essential role in making ready vision knowledge in people. The vision framework may be a basic part of the body's overall framework, performing essential capacities and better vision abilities. This study is planned to look at the reasons for early vision misfortune and to study additional about the neural dynamics of the vision cortex.This information is essential for a variety of recovery and treatment options.

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Auditory Attention State Decoding for the Quiet and Hypothetical Environment: A Comparison Between bLSTM and SVM

Cited by 19 publications

References 25 publications

A Recommender System for Adaptive Examination Preparation using Pearson Correlation Collaborative Filtering

A Recommender System for Adaptive Examination Preparation using Pearson Correlation Collaborative Filtering

Transfer Learning Approach Applied to Data Imputation

The Ability to Detect Vision Loss from the Visual Cortex Using iEEG is a Key Advance in the Treatment of The Condition

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