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ISSN: 2666-3074

Fake News Classification using transformer based enhanced LSTM and BERT

•Fake News has been a concern all over the world and social media has only amplified this phenomenon and it has been affecting the world on a large scale as these are targeted to sway the decisions...

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A review on object detection in unmanned aerial vehicle surveillance

•In this paper, a detailed literature review has been conducted focusing on object detection and tracking using UAVs concerning different applications.•Contribution: Object detection methods applied...

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Medical image fusion method by deep learning

•Deep learning models can extract the most effective features automatically from data to overcome the difficulty of manual design. In this paper, deep learning model is intended to be introduced into...

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Machine learning based diabetes prediction and development of smart web application

•The goal of this work is to find effective machine learning based classifier models for detecting diabetes in individuals utilizing clinical data.•The results of this study suggest that an appropriate...

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Facial expression recognition via ResNet-50

•We propose a deep residual network ResNet-50 for facial expression recognition.•Convolution operation is used to extract features and pooling is used to reduce dimension of features.•BN and activation...

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Deep learning based assistive technology on audio visual speech recognition for hearing impaired

•Assistive technology on speech to text conversion for hearing impaired students.•Performance of the system boost using multi modal features.•Lip reading architecture capture visual speech recognition.•Deep...

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An ensemble approach for classification and prediction of diabetes mellitus using soft voting classifier

•World Health Organization (WHO) reported globally that adult diabetes patients have nearly doubled since 1980, rising from 4.7% to 8.5%. In 2012, 1.5 million people died due to diabetes.•The early...

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A review of the application of deep learning in the detection of Alzheimer's disease

•Alzheimer's disease (AD) detection using deep learning was reviewed.•Patch based and ROI based feature extraction methods are used most frequently and effectively.•Preprocessing technology is key to...

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An analysis of the ethical challenges of blockchain-enabled E-healthcare applications in 6G networks

•In this milieu, an attempt has been made to identify the parameters of ethical challenges associated with blockchain adoption.•The paper also contributes to the extant body of knowledge by presenting...

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Exploring generative adversarial networks and adversarial training

•Generative Adversarial Networks (GANs) are notorious to train. Research has been conducted in various angles to address the challenges.•Classifiers or Discriminators are susceptible to adversarial...

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Smart Home Security Solutions using Facial Authentication and Speaker Recognition through Artificial Neural Networks

•Holistic solution for Smart Home Security which helps in improving privacy and security using two independent and emerging technologies of Facial authentication and Speech Recognition.•The entire process...

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1D Convolution approach to human activity recognition using sensor data and comparison with machine learning algorithms

•Novel 1D convolutional neural network model for Human Activity Recognition proposed.•Performance analysis of the classical ML models.•Classical ML models compared with proposed model.•SVM and 1D convolution...

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Microarray cancer feature selection: Review, challenges and research directions

Microarray technology has become an emerging trend in the domain of genetic research in which many researchers employ to study and investigate the levels of genes’ expression in a given organism. Microarray...

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Application of machine learning based algorithm for prediction of malnutrition among women in Bangladesh

•Determine the prevalence of malnutrition among women in Bangladesh.•Identification of the risk factors of malnutrition using logistic regression.•Prediction of malnutrition based on machine learning...

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Type 2: Diabetes mellitus prediction using Deep Neural Networks classifier

•The frameworks evolved for support to medical experiments and algorithms for accurate prediction.•An unsupervised learning approach used for accurate prediction of the dataset of pima indian diabetes.•Early...

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A novel hybrid methodology for computing semantic similarity between sentences through various word senses

In the area of natural language processing, measuring sentence similarity is an essential problem. Searching for semantic meaning in natural language is a related issue. The task of measuring sentence...

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Affective state and learning environment based analysis of students’ performance in online assessment

•Paper identifies effect of various factors on performance of students.•Sleep hours and energy level had no effect on the performance.•Mood and time of day had an impact on students' performance.•Analysis...

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Developing Turkish sentiment analysis models using machine learning and e-commerce data

•New models for predicting the sentiments expressed via Turkish texts have been proposed.•Sentiment analysis models were built using SVM, RF, DT, LR, and KNN classifiers.•Reviews are classified as positive,...

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A survey on deep learning models for wireless capsule endoscopy image analysis

•Review on Deep learning models in Wireless Capsule Endoscopy image analysis in the aspect of Dataset used, Model Trustworthiness and Domain Knowledge inclusion.•Semi Supervised Model in Capsule Endoscopy...

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Tackling Requirements Uncertainty in Software Projects: A Cognitive Approach

•Various uncertainty types and sources/causes of uncertainty.•How various uncertainty types are related to each other?•What are the positive and negative impacts of these uncertainty types?•Various...

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A three-stage ensemble boosted convolutional neural network for classification and analysis of COVID-19 chest x-ray images

•A three-stage ensemble boosted convolutional neural network model is applied for identification and classification of COVID-19.•CNN model is employed to extract the features from the training dataset...

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Contact-free wheat mildew detection with commodity wifi

•We verify the feasibility of using WiFi CSI amplitude information for wheat mildew detection. To the best of our knowledge, this is the first work that uses WiFi based RF sensing for wheat mildew detection.•We...

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Gray level co-occurrence matrix and extreme learning machine for Covid-19 diagnosis

•In this paper, we propose a hybrid model which uses gray co-occurrence matrix as feature extractor and extreme learning machine as classifier.•Compared with the traditional forward neural network,...

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Developing bug severity prediction models using word2vec

•Developing a semi-automated bug prediction model to assist developers in the analysis of bug severity levels.•Empirical evaluation of the effect of using word embedding (word2vec) on the performance...

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Classification of Indian media titles using deep learning techniques

•The goal of the paper is to identify the language of Indian media titles (Song names, movie titles) for automatic speech recognition training data.•Transliterated data of songs and movie titles were...

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