Salim KhazemGeorgiaTech - CNRS | CentraleSupélec
Salim Khazem
Doctor of Engineering
PhD Student at GeorgiaTech - CNRS | CentraleSupélec
About
6
Publications
485
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16
Citations
Introduction
Field : Deep learning, Machine learning, Computer Vision, Artificial Intelligence, Neural Network
Publications
Publications (6)
Plastic waste in aquatic environments poses severe risks to marine life and human health. Autonomous robots can be utilized to collect floating waste, but they require accurate object identification capability. While deep learning has been widely used as a powerful tool for this task, its performance is significantly limited by outdoor light condit...
The quality of a wood log in the wood industry depends heavily on the presence of both outer and inner defects, including inner knots that are a result of the growth of tree branches. Today, locating the inner knots require the use of expensive equipment such as X-ray scanners. In this paper, we address the task of predicting the location of inner...
The quality of a wood log in the wood industry depends heavily on the presence of both outer and inner defects, including inner knots that are a result of the growth of tree branches. Today, locating the inner knots require the use of expensive equipment such as X-ray scanners. In this paper, we address the task of predicting the location of inner...
According to the industry, the value of wood logs is heavily influenced by their internal structure, particularly the distribution of knots within the trees. Nowadays, CT scanners combined with classical computer vision approach are the most common tool for obtaining reliable and accurate images of the interior structure of trees. Knowing where the...
Calibration is still an important issue for user experience in Brain-Computer Interfaces (BCI). Common experimental designs often involve a lengthy training period that raises the cognitive fatigue, before even starting to use the BCI. Reducing or suppressing this subject-dependent calibration is possible by relying on advanced machine learning tec...
Calibration is still an important issue for user
experience in Brain-Computer Interfaces (BCI). Common experimental designs often involve a lengthy training period that
raises the cognitive fatigue, before even starting to use the BCI.
Reducing or suppressing this subject-dependent calibration is
possible by relying on advanced machine learning tec...