[HTML][HTML] Deep learning classifiers for hyperspectral imaging: A review
Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
Artificial intelligence for mental health and mental illnesses: an overview
Abstract Purpose of Review Artificial intelligence (AI) technology holds both great promise to
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …
Survey on deep learning with class imbalance
JM Johnson, TM Khoshgoftaar - Journal of big data, 2019 - Springer
The purpose of this study is to examine existing deep learning techniques for addressing
class imbalanced data. Effective classification with imbalanced data is an important area of …
class imbalanced data. Effective classification with imbalanced data is an important area of …
Concepts of artificial intelligence for computer-assisted drug discovery
X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …
opportunities for the discovery and development of innovative drugs. Various machine …
[HTML][HTML] Industry 5.0—A human-centric solution
S Nahavandi - Sustainability, 2019 - mdpi.com
Staying at the top is getting tougher and more challenging due to the fast-growing and
changing digital technologies and AI-based solutions. The world of technology, mass …
changing digital technologies and AI-based solutions. The world of technology, mass …
Comprehensive review of artificial neural network applications to pattern recognition
The era of artificial neural network (ANN) began with a simplified application in many fields
and remarkable success in pattern recognition (PR) even in manufacturing industries …
and remarkable success in pattern recognition (PR) even in manufacturing industries …
Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …
a key enabler and a leading infrastructure provider in the information and communication …
Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0
The so-called “smartization” of manufacturing industries has been conceived as the fourth
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods
Floods around the world are having devastating effects on human life and property. In this
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …
paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS …
Machine learning algorithms for wireless sensor networks: A survey
Wireless sensor network (WSN) is one of the most promising technologies for some real-
time applications because of its size, cost-effective and easily deployable nature. Due to …
time applications because of its size, cost-effective and easily deployable nature. Due to …