[HTML][HTML] Deep learning: a comprehensive overview on techniques, taxonomy, applications and research directions

IH Sarker - SN computer science, 2021‏ - Springer
Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is
nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or …

[HTML][HTML] IoT anomaly detection methods and applications: A survey

A Chatterjee, BS Ahmed - Internet of Things, 2022‏ - Elsevier
Ongoing research on anomaly detection for the Internet of Things (IoT) is a rapidly
expanding field. This growth necessitates an examination of application trends and current …

Machine learning for anomaly detection: A systematic review

AB Nassif, MA Talib, Q Nasir, FM Dakalbab - Ieee Access, 2021‏ - ieeexplore.ieee.org
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

Using the internet of things in smart energy systems and networks

T Ahmad, D Zhang - Sustainable Cities and Society, 2021‏ - Elsevier
Private businesses and policymakers are accelerating the deployment and advancement of
smart grid technology innovations that can support smart energy systems. Technological …

Automated DDOS attack detection in software defined networking

N Ahuja, G Singal, D Mukhopadhyay… - Journal of Network and …, 2021‏ - Elsevier
Abstract Software-Defined Networking (SDN) is a networking paradigm that has redefined
the term network by making the network devices programmable. SDN helps network …

An optimized dense convolutional neural network model for disease recognition and classification in corn leaf

A Waheed, M Goyal, D Gupta, A Khanna… - … and Electronics in …, 2020‏ - Elsevier
An optimized dense convolutional neural network (CNN) architecture (DenseNet) for corn
leaf disease recognition and classification is proposed in this paper. Corn is one of the most …

[HTML][HTML] Explainable AI for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects

IH Sarker, H Janicke, A Mohsin, A Gill, L Maglaras - ICT Express, 2024‏ - Elsevier
Digital twins (DTs) are an emerging digitalization technology with a huge impact on today's
innovations in both industry and research. DTs can significantly enhance our society and …

Smart anomaly detection in sensor systems: A multi-perspective review

L Erhan, M Ndubuaku, M Di Mauro, W Song, M Chen… - Information …, 2021‏ - Elsevier
Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …

A novel PCA–whale optimization-based deep neural network model for classification of tomato plant diseases using GPU

TR Gadekallu, DS Rajput, MPK Reddy… - Journal of Real-Time …, 2021‏ - Springer
The human population is growing at a very rapid scale. With this progressive growth, it is
extremely important to ensure that healthy food is available for the survival of the inhabitants …

Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review

B Jena, S Saxena, GK Nayak, L Saba, N Sharma… - Computers in Biology …, 2021‏ - Elsevier
Background Artificial intelligence (AI) has served humanity in many applications since its
inception. Currently, it dominates the imaging field—in particular, image classification. The …