A review of the Artificial Intelligence (AI) based techniques for estimating reference evapotranspiration: Current trends and future perspectives
Reference Evapotranspiration (ET o) is a complex, dynamic and non-linear hydrological
process. Accurate estimation of ET o has long been an eminent topic of interest in the …
process. Accurate estimation of ET o has long been an eminent topic of interest in the …
An empirical survey of data augmentation for time series classification with neural networks
In recent times, deep artificial neural networks have achieved many successes in pattern
recognition. Part of this success can be attributed to the reliance on big data to increase …
recognition. Part of this success can be attributed to the reliance on big data to increase …
Time series forecasting of COVID-19 transmission in Canada using LSTM networks
VKR Chimmula, L Zhang - Chaos, solitons & fractals, 2020 - Elsevier
Abstract On March 11 th 2020, World Health Organization (WHO) declared the 2019 novel
corona virus as global pandemic. Corona virus, also known as COVID-19 was first …
corona virus as global pandemic. Corona virus, also known as COVID-19 was first …
Human-factors-in-driving-loop: Driver identification and verification via a deep learning approach using psychological behavioral data
Driver identification has been popular in the field of driving behavior analysis, which has a
broad range of applications in anti-thief, driving style recognition, insurance strategy, and …
broad range of applications in anti-thief, driving style recognition, insurance strategy, and …
A federated learning system with enhanced feature extraction for human activity recognition
With the rapid growth of mobile devices, wearable sensor-based human activity recognition
(HAR) has become one of the hottest topics in the Internet of Things. However, it is …
(HAR) has become one of the hottest topics in the Internet of Things. However, it is …
Clustering-based speech emotion recognition by incorporating learned features and deep BiLSTM
Emotional state recognition of a speaker is a difficult task for machine learning algorithms
which plays an important role in the field of speech emotion recognition (SER). SER plays a …
which plays an important role in the field of speech emotion recognition (SER). SER plays a …
RTFN: A robust temporal feature network for time series classification
Time series data usually contains local and global patterns. Most of the existing feature
networks focus on local features rather than the relationships among them. The latter is also …
networks focus on local features rather than the relationships among them. The latter is also …
Deep-net: A lightweight CNN-based speech emotion recognition system using deep frequency features
Artificial intelligence (AI) and machine learning (ML) are employed to make systems smarter.
Today, the speech emotion recognition (SER) system evaluates the emotional state of the …
Today, the speech emotion recognition (SER) system evaluates the emotional state of the …
Short-term wind speed forecasting based on long short-term memory and improved BP neural network
G Chen, B Tang, X Zeng, P Zhou, P Kang… - International Journal of …, 2022 - Elsevier
Accurate and reasonable wind speed prediction system has a significant impact on the
utilization of wind energy. A novel combination forecasting model based on Long Short …
utilization of wind energy. A novel combination forecasting model based on Long Short …
Detection of non-stationary GW signals in high noise from Cohen's class of time–frequency representations using deep learning
Analysis of non-stationary signals in a noisy environment is a challenging research topic in
many fields often requiring simultaneous signal decomposition in the time and frequency …
many fields often requiring simultaneous signal decomposition in the time and frequency …