Automatic speech recognition (asr) systems for children: A systematic literature review
Automatic speech recognition (ASR) is one of the ways used to transform acoustic speech
signals into text. Over the last few decades, an enormous amount of research work has been …
signals into text. Over the last few decades, an enormous amount of research work has been …
Comprehensive analysis of network slicing for the developing commercial needs and networking challenges
S Zahoor, I Ahmad, MTB Othman, A Mamoon… - Sensors, 2022 - mdpi.com
Network slicing (NS) is one of the most prominent next-generation wireless cellular
technology use cases, promising to unlock the core benefits of 5G network architecture by …
technology use cases, promising to unlock the core benefits of 5G network architecture by …
Depression recognition based on the reconstruction of phase space of EEG signals and geometrical features
Depression is a mental disorder that continues to make life difficult or impossible for a
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
Botnet attack detection in iot using machine learning
There are an increasing number of Internet of Things (IoT) devices connected to the network
these days, and due to the advancement in technology, the security threads and …
these days, and due to the advancement in technology, the security threads and …
[HTML][HTML] Machine learning and Natural Language Processing of social media data for event detection in smart cities
Social media data analysis in a smart city context can represent an efficacious instrument to
inform decision making. The manuscript strives to leverage the power of Natural Language …
inform decision making. The manuscript strives to leverage the power of Natural Language …
Automated detection of Alzheimer's via hybrid classical quantum neural networks
Deep Neural Networks have offered numerous innovative solutions to brain-related
diseases including Alzheimer's. However, there are still a few standpoints in terms of …
diseases including Alzheimer's. However, there are still a few standpoints in terms of …
Identification of motor and mental imagery EEG in two and multiclass subject-dependent tasks using successive decomposition index
The development of fast and robust brain–computer interface (BCI) systems requires non-
complex and efficient computational tools. The modern procedures adopted for this purpose …
complex and efficient computational tools. The modern procedures adopted for this purpose …
Smart android based home automation system using internet of things (IoT)
Recently, home automation system has getting significant attention because of the fast and
advanced technology, making daily living more convenient. Almost everything has been …
advanced technology, making daily living more convenient. Almost everything has been …
An improved residential electricity load forecasting using a machine-learning-based feature selection approach and a proposed integration strategy
Load forecasting (LF) has become the main concern in decentralized power generation
systems with the smart grid revolution in the 21st century. As an intriguing research topic, it …
systems with the smart grid revolution in the 21st century. As an intriguing research topic, it …
On disharmony in batch normalization and dropout methods for early categorization of Alzheimer's disease
Alzheimer's disease (AD) is a global health issue that predominantly affects older people. It
affects one's daily activities by modifying neural networks in the brain. AD is categorized by …
affects one's daily activities by modifying neural networks in the brain. AD is categorized by …