Understanding of machine learning with deep learning: architectures, workflow, applications and future directions
MM Taye - Computers, 2023 - mdpi.com
In recent years, deep learning (DL) has been the most popular computational approach in
the field of machine learning (ML), achieving exceptional results on a variety of complex …
the field of machine learning (ML), achieving exceptional results on a variety of complex …
Understanding O-RAN: Architecture, interfaces, algorithms, security, and research challenges
The Open Radio Access Network (RAN) and its embodiment through the O-RAN Alliance
specifications are poised to revolutionize the telecom ecosystem. O-RAN promotes …
specifications are poised to revolutionize the telecom ecosystem. O-RAN promotes …
[HTML][HTML] Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges
The growth of the construction industry is severely limited by the myriad complex challenges
it faces such as cost and time overruns, health and safety, productivity and labour shortages …
it faces such as cost and time overruns, health and safety, productivity and labour shortages …
CNN variants for computer vision: History, architecture, application, challenges and future scope
Computer vision is becoming an increasingly trendy word in the area of image processing.
With the emergence of computer vision applications, there is a significant demand to …
With the emergence of computer vision applications, there is a significant demand to …
Study on artificial intelligence: The state of the art and future prospects
C Zhang, Y Lu - Journal of Industrial Information Integration, 2021 - Elsevier
In the world, the technological and industrial revolution is accelerating by the widespread
application of new generation information and communication technologies, such as AI, IoT …
application of new generation information and communication technologies, such as AI, IoT …
Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
A comparative study of deep learning and Internet of Things for precision agriculture
Precision farming is made possible by rapid advances in deep learning (DL) and the internet
of things (IoT) for agriculture, allowing farmers to upgrade their agriculture operations to …
of things (IoT) for agriculture, allowing farmers to upgrade their agriculture operations to …
Part of speech tagging: a systematic review of deep learning and machine learning approaches
A Chiche, B Yitagesu - Journal of Big Data, 2022 - Springer
Natural language processing (NLP) tools have sparked a great deal of interest due to rapid
improvements in information and communications technologies. As a result, many different …
improvements in information and communications technologies. As a result, many different …
A survey of deep learning techniques for weed detection from images
The rapid advances in Deep Learning (DL) techniques have enabled rapid detection,
localisation, and recognition of objects from images or videos. DL techniques are now being …
localisation, and recognition of objects from images or videos. DL techniques are now being …
A silicon photonic–electronic neural network for fibre nonlinearity compensation
In optical communication systems, fibre nonlinearity is the major obstacle in increasing the
transmission capacity. Typically, digital signal processing techniques and hardware are …
transmission capacity. Typically, digital signal processing techniques and hardware are …