A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective
Artificial intelligence (AI) can bring both opportunities and challenges to human resource
management (HRM). While scholars have been examining the impact of AI on workplace …
management (HRM). While scholars have been examining the impact of AI on workplace …
[HTML][HTML] CNN-based burned area mapping using radar and optical data
In this paper, we present an in-depth analysis of the use of convolutional neural networks
(CNN), a deep learning method widely applied in remote sensing-based studies in recent …
(CNN), a deep learning method widely applied in remote sensing-based studies in recent …
Completing the machine learning saga in fractional snow cover estimation from MODIS Terra reflectance data: Random forests versus support vector regression
S Kuter - Remote Sensing of Environment, 2021 - Elsevier
This study; i) investigates the suitability of two frequently employed machine learning
algorithms in remote sensing, namely, random forests (RFs) and support vector regression …
algorithms in remote sensing, namely, random forests (RFs) and support vector regression …
An IoT and machine learning‐based routing protocol for reconfigurable engineering application
Y Natarajan, K Srihari, G Dhiman… - IET …, 2022 - Wiley Online Library
With new telecommunications engineering applications, the cognitive radio (CR) network‐
based internet of things (IoT) resolves the bandwidth problem and spectrum problem …
based internet of things (IoT) resolves the bandwidth problem and spectrum problem …
Artificial intelligence approach for tomato detection and mass estimation in precision agriculture
Application of computer vision and robotics in agriculture requires sufficient knowledge and
understanding of the physical properties of the object of interest. Yield monitoring is an …
understanding of the physical properties of the object of interest. Yield monitoring is an …
Prediction of arctic sea ice concentration using a fully data driven deep neural network
J Chi, H Kim - Remote Sensing, 2017 - mdpi.com
The Arctic sea ice is an important indicator of the progress of global warming and climate
change. Prediction of Arctic sea ice concentration has been investigated by many disciplines …
change. Prediction of Arctic sea ice concentration has been investigated by many disciplines …
Natural gas consumption forecast with MARS and CMARS models for residential users
Prediction natural gas consumption is indispensable for efficient system operation and
required for planning decisions at natural gas Local Distribution Companies (LDCs) …
required for planning decisions at natural gas Local Distribution Companies (LDCs) …
Exploring artificial neural networks efficiency in tiny wearable devices for human activity recognition
The increasing diffusion of tiny wearable devices and, at the same time, the advent of
machine learning techniques that can perform sophisticated inference, represent a valuable …
machine learning techniques that can perform sophisticated inference, represent a valuable …
An intelligent ensemble classification method based on multi-layer perceptron neural network and evolutionary algorithms for breast cancer diagnosis
S Talatian Azad, G Ahmadi… - Journal of Experimental & …, 2022 - Taylor & Francis
Nowadays, breast cancer is one of the leading causes of women's death in the world. If
breast cancer is detected at the initial stages, it can ensure long-term survival. Numerous …
breast cancer is detected at the initial stages, it can ensure long-term survival. Numerous …
Retrieval of fractional snow covered area from MODIS data by multivariate adaptive regression splines
In this paper, a novel approach to estimate fractional snow cover (FSC) from MODIS data in
a complex and heterogeneous Alpine terrain is represented by using a state-of-the-art …
a complex and heterogeneous Alpine terrain is represented by using a state-of-the-art …