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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...

Integrating artificial intelligence and quantum computing: A systematic literature review of features and applications

•Novel synthesis of 30+ studies detailing the state-of-the-art in the integration of AI and QC, highlighting quantum machine learning, optimization techniques, and sector-specific applications.•Identification...

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...

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...

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...

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...

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...

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...

Development of a feature vector for accurate breast cancer detection in mammographic images

Breast cancer remains one of the leading causes of mortality among women, making early and accurate detection crucial for effective treatment. Despite the extensive use of deep learning models in mammographic...

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...

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...

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,...

Transforming legal texts into computational logic: Enhancing next generation public sector automation through explainable AI decision support

This research presents a novel approach for translating legal texts into machine-executable computational logic to support the automation of public sector processes. Recognizing the high-stakes implications...

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...

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...

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...

Analysis of emotional tendencies and discourse patterns in VKontakte social comments based on Nvivo12 encoding

•Influence of VKontakte Comments: Comments on VKontakte impact government policies, public attitudes, and international relations, making them crucial for analysis.•Emotional Tendencies During COVID-19...

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...

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...

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...

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...

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...

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