[HTML][HTML] Facial expression recognition via ResNet-50
B Li, D Lima - International Journal of Cognitive Computing in …, 2021 - Elsevier
As one of the most important directions in the field of computer vision, facial emotion
recognition plays an important role in people's daily work and life. Human emotion …
recognition plays an important role in people's daily work and life. Human emotion …
An integrated mediapipe-optimized GRU model for Indian sign language recognition
Sign language recognition is challenged by problems, such as accurate tracking of hand
gestures, occlusion of hands, and high computational cost. Recently, it has benefited from …
gestures, occlusion of hands, and high computational cost. Recently, it has benefited from …
Multitarget prediction and optimization of pure electric vehicle tire/road airborne noise sound quality based on a knowledge-and data-driven method
H Huang, TC Lim, J Wu, W Ding, J Pang - Mechanical Systems and Signal …, 2023 - Elsevier
With the promotion of pure electric vehicles (PEVs), the overall interior noise level has been
gradually reduced. Tire/road noise is increasingly becoming noticeable in PEVs and …
gradually reduced. Tire/road noise is increasingly becoming noticeable in PEVs and …
UzADL: Anomaly detection and localization using graph Laplacian matrix-based unsupervised learning method
Visual inspection is an essential quality control process in industrial businesses. It is usually
automated due to its tedious procedure. An automated visual inspection (AVI) attempts to …
automated due to its tedious procedure. An automated visual inspection (AVI) attempts to …
Consecutive multiscale feature learning-based image classification model
Extracting useful features at multiple scales is a crucial task in computer vision. The
emergence of deep-learning techniques and the advancements in convolutional neural …
emergence of deep-learning techniques and the advancements in convolutional neural …
Effective feature engineering technique for heart disease prediction with machine learning
Heart failure is a chronic disease affecting millions worldwide. An efficient machine learning-
based technique is needed to predict heart failure health status early and take necessary …
based technique is needed to predict heart failure health status early and take necessary …
Bayesian optimized multilayer perceptron neural network modelling of biochar and syngas production from pyrolysis of biomass-derived wastes
Biochar and syngas are important products of pyrolysis that can be employed for a wide
range of applications such as catalysts for biodiesel production, wastewater treatment, and …
range of applications such as catalysts for biodiesel production, wastewater treatment, and …
A genetic algorithm-assisted deep learning approach for crop yield prediction
The world population continues to increase which imposes rising demand in agriculture
production. How to improve crop breeding to feed the growing population is a significant …
production. How to improve crop breeding to feed the growing population is a significant …
Radiant heating systems control in buildings via inverse conformable artificial neural networks and optimization techniques
This study introduces an innovative methodology that integrates Inverse Conformable
Artificial Neural Networks (CANNi) with Genetic Algorithms (GA) or Particle Swarm …
Artificial Neural Networks (CANNi) with Genetic Algorithms (GA) or Particle Swarm …
Estimation of concrete materials uniaxial compressive strength using soft computing techniques
This study addresses a critical gap in concrete strength prediction by conducting a
comparative analysis of three deep learning algorithms: convolutional neural networks …
comparative analysis of three deep learning algorithms: convolutional neural networks …