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ISSN: 2666-3074

Automatic Speech Recognition: A survey of deep learning techniques and approaches

Significant research has been conducted during the last decade on the application of machine learning for speech processing, particularly speech recognition. However, in recent years, deep learning...

Deep learning for object recognition: A comprehensive review of models and algorithms

The rapid advancements in artificial intelligence (AI) and machine learning (ML) have significantly enhanced progress in computer vision, opening doors to innovative technological possibilities and...

Text clustering with large language model embeddings

Text clustering is an important method for organising the increasing volume of digital content, aiding in the structuring and discovery of hidden patterns in uncategorised data. The effectiveness of...

An ensemble machine learning based bank loan approval predictions system with a smart application

Banks rely heavily on loans as a primary source of revenue; however, distinguishing deserving applicants who will reliably repay loans presents an ongoing challenge. Conventional selection processes...

Exploring the potential of 3D scanning in Industry 4.0: An overview

•A 3D scanner is a non-contact, non-destructive digital device that uses a light/laser source to accurately capture the shape of a physical object into computer-aided design (CAD) data.•It generates...

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...

Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies

In the rapidly advancing era of educational technology, customized learning materials have the potential to enhance individuals’ learning capacities. This research endeavors to devise an effective method...

Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN

Human activity recognition (HAR) plays a crucial role in assisting the elderly and individuals with vascular dementia by providing support and monitoring for their daily activities. This paper presents...

Clock synchronization in industrial Internet of Things and potential works in precision time protocol: Review, challenges and future directions

•This research investigated and analyzed IEEE 1588 PTP-based synchronization methods for IoT and industrial applications in depth.•The efficiency and working principle of different time synchronization...

Fake review detection using transformer-based enhanced LSTM and RoBERTa

•Comprehensive examination of various methodologies in the identification of false reviews.•A novel and practical approach that leverages transformer architecture to identify fake reviews.•A comprehensive...

Segmentation and classification of brain tumor using 3D-UNet deep neural networks

•The proposed work considers an image registration model, a 3D U-Net model, for the volumetric segmentation of the brain tumor.•The next step is the classification of the brain tumors into meningioma,...

Adaptive traffic prediction model using Graph Neural Networks optimized by reinforcement learning

Traffic prediction is critical for urban planning and transportation management, with significant implications for congestion reduction, resource allocation, and sustainability. Traditional statistical...

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...

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...

Technology-Assisted Language Learning Adaptive Systems: A Comprehensive Review

•Comprehensive review of trends and development of technology-assisted language learning (TALL) adaptive systems is presented.•Resulting studies have been analyzed from three dimensions viz. spatial...

Application of the vision-based deep learning technique for waste classification using the robotic manipulation system

To maintain a green society, efficient waste management is crucial. Traditional manual trash sorting presents several challenges, including inaccuracies in classification and potential health risks...

Multi-class sentiment classification on Bengali social media comments using machine learning

•In recent years, immense work has been done on sentiment analysis directed towards the binary (positive, negative) or ternary (positive, neutral, negative) classification. Due to the complexity of...

Data-driven strategies for digital native market segmentation using clustering

The rapid growth of internet users and social networking sites presents significant challenges for entrepreneurs and marketers. Understanding the evolving behavioral and psychological patterns across...

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...

Image cyberbullying detection and recognition using transfer deep machine learning

•This research addresses shortcomings in existing literature and offers a new perspective in the fight against cyberbullying.•It proposes a hybrid approach that utilizes the strengths of both deep learning...

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...

Integration of Artificial Intelligence and Wearable Internet of Things for Mental Health Detection

The integration of Artificial Intelligence (AI) and Wearable Internet of Things (WIoT) for mental health detection is a promising area of research with the potential to revolutionize mental health monitoring...

A survey of large-scale graph-based semi-supervised classification algorithms

•Carefully introduces the process of graph-based semi-supervised classification algorithms for the large-scale problem.•A new perspective from granular calculation reveals the mechanism to improve the...

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...

Deep learning-based approaches for abusive content detection and classification for multi-class online user-generated data

•an abusive language detection model that perform multiclass classification of offensive language.•experimented with five deep learning models: Bi-LSTM, LSTM, Bi-GRU, GRU, and multi-dense LSTM.•dataset...

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