Recent trends in deep learning based personality detection
Recently, the automatic prediction of personality traits has received a lot of attention.
Specifically, personality trait prediction from multimodal data has emerged as a hot topic …
Specifically, personality trait prediction from multimodal data has emerged as a hot topic …
[HTML][HTML] Advances in multimodal emotion recognition based on brain–computer interfaces
With the continuous development of portable noninvasive human sensor technologies such
as brain–computer interfaces (BCI), multimodal emotion recognition has attracted increasing …
as brain–computer interfaces (BCI), multimodal emotion recognition has attracted increasing …
COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis
Aim: COVID-19 is a disease caused by a new strain of coronavirus. Up to 18th October
2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 …
2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 …
Multisensor feature fusion for bearing fault diagnosis using sparse autoencoder and deep belief network
To assess health conditions of rotating machinery efficiently, multiple accelerometers are
mounted on different locations to acquire a variety of possible faults signals. The statistical …
mounted on different locations to acquire a variety of possible faults signals. The statistical …
Biometrics recognition using deep learning: A survey
In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …
Deep feature fusion for VHR remote sensing scene classification
The rapid development of remote sensing technology allows us to get images with high and
very high resolution (VHR). VHR imagery scene classification has become an important and …
very high resolution (VHR). VHR imagery scene classification has become an important and …
Remote sensing scene classification by gated bidirectional network
Remote sensing (RS) scene classification is a challenging task due to various land covers
contained in RS scenes. Recent RS classification methods demonstrate that aggregating the …
contained in RS scenes. Recent RS classification methods demonstrate that aggregating the …
[HTML][HTML] Information fusion and artificial intelligence for smart healthcare: a bibliometric study
With the fast progress in information technologies and artificial intelligence (AI), smart
healthcare has gained considerable momentum. By using advanced technologies like AI …
healthcare has gained considerable momentum. By using advanced technologies like AI …
FEC: A feature fusion framework for SAR target recognition based on electromagnetic scattering features and deep CNN features
The active recognition of interesting targets has been a vital issue for synthetic aperture
radar (SAR) systems. The SAR recognition methods are mainly grouped as follows …
radar (SAR) systems. The SAR recognition methods are mainly grouped as follows …
A feature aggregation convolutional neural network for remote sensing scene classification
Remote sensing scene classification (RSSC) refers to inferring semantic labels based on the
content of the remote sensing scenes. Recently, most works take the pretrained …
content of the remote sensing scenes. Recently, most works take the pretrained …