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Open AccessSSO-CCNN: A Correlation-Based Optimized Deep CNN for Brain Tumor Classification Using Sampled PGGAN
Recently, new advancements in technologies have promoted the classification of brain tumors at the early stages to reduce mortality and disease severity. Hence, there is a need for an automatic classification ...
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Article
Ontology-Based Layered Rule-Based Network Intrusion Detection System for Cybercrimes Detection
The need to secure Internet applications on global networks has become an important task due to the ever-increasing cybercrimes. A common technique for identifying intrusions in computer networks is the Networ...
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Article
Open AccessAlzheimer’s Disease Detection via Multiscale Feature Modelling Using Improved Spatial Attention Guided Depth Separable CNN
Early detection of Alzheimer's disease (AD) is critical due to its rising prevalence. AI-aided AD diagnosis has grown for decades. Most of these systems use deep learning using CNN. However, a few concerns mus...
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Article
Open AccessMachine learning-empowered sleep staging classification using multi-modality signals
The goal is to enhance an automated sleep staging system's performance by leveraging the diverse signals captured through multi-modal polysomnography recordings. Three modalities of PSG signals, namely electro...
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Article
Early Malignant Mesothelioma Detection Using Ensemble of Naive Bayes Under Decorate Ensemble Framework
The growing role of machine learning in early malignant mesothelioma highlights the significance of this study. This study analyzes and suggests an ensemble approach using the Decorate ensemble where the famou...
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Article
AutoML Trading: A Rule-Based Model to Predict the Bull and Bearish Market
Many researchers from different fields have tried to figure out how to forecast the future and trade on the share market since it is hard to accomplish because the market is so complicated. Machine-learning te...
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Article
Bot-FFX: A Robust and Efficient Framework for Fast Flux Botnet (FFB) Detection
Fast Flux Botnet (FFB) poses a significant threat as an advanced method employed by cybercriminals for orchestrating distributed malicious attacks. Existing FFB detection systems face challenges such as vulner...
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Article
Big data analytics enabled deep convolutional neural network for the diagnosis of cancer
Artificial intelligence (AI) has been shown to be a formidable instrument in managing Big Healthcare Data, and it has seen considerable success in bioinformatics. The advancement of big data in biological scie...
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Chapter
Conclusion and Future Directions
HADR is an emerging field of research. In our survey, we minutely categorized different types of activities into normal, abnormal and suspicious types according to their criticality. We outlined some of the ke...
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Introduction
The Human Activity Detection and Recognition (HADR) system is a crucial computer vision application. It focuses on the creation of a number of tools or techniques that use computer vision and AI to identify a ...
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Basic Framework of HADR
A unified framework for develo** or understanding a model for the HADR is highly essential. This will help in understanding each and every individual step involved in develo** a new system or understanding...
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Book
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Applications for HADR
The HADR has various applications in our day-to-day lives using different sensors ranging from vision-based to non-vision-based. Understanding the progress of each of the applications of HADR is highly essenti...
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Datasets
Modern research in the field of Human Activity Recognition primarily revolves around Machine Learning and Deep Learning, due to their substantial advantages in terms of adaptability, precision, and enhanced pr...
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Comparative Analysis
A comparative analysis of several state-of-the-art approaches is a critical measure for research. It helps in evaluating different techniques based on several traits. Thus, the main objective of this chapter i...
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Article
Multi-Label Learning Model for Diabetes Disease Comorbidity
Multi-label modeling of clinical data is a challenging classification problem especially for diseases with comorbidities. The complexity of the dataset makes it difficult to detect hidden pattern and infer use...
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Article
Open AccessThe ForEx++ based decision tree ensemble approach for robust detection of Parkinson’s disease
The progressive reduction of dopaminergic neurons in the human brain, especially at the substantia nigra is one of the principal causes of Parkinson’s Disease (PD). Voice alteration is one of the earliest symp...
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Article
Open AccessStatistical Analysis of Design Aspects of Various YOLO-Based Deep Learning Models for Object Detection
Object detection is a critical and complex problem in computer vision, and deep neural networks have significantly enhanced their performance in the last decade. There are two primary types of object detectors...
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Article
Open AccessA Multi-level Random Forest Model-Based Intrusion Detection Using Fuzzy Inference System for Internet of Things Networks
Intrusion detection (ID) methods are security frameworks designed to safeguard network information systems. The strength of an intrusion detection method is dependent on the robustness of the feature selection me...
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Article
Breast cancer diagnosis based on hybrid rule-based feature selection with deep learning algorithm
One of the leading causes of death among women is breast cancer. However, it has been established that early diagnosis with accurate results can ensure the prolonged survival of patients even with the illness....
