报告人：Prof. Ali Djafari
报告时间：2024年11月8日下午14:30-15:30
报告地点：机械楼D526
报告摘要：
Neural Networks (NN) has been used in many area with great succes. When a NN’s structure (Model) is given, during the training steps, the parameters of the model is determined using an appropriate criterion and an optimization algoriothm (Training). Then, the trained model can be used for the prediction or iference step (Testing). As there are also many hyperparameters, related to the optimization criteria and optimization algorithms, a validation step is necessary before its final use. One of the great difficulties is the choice of the NN’s structure. Even if there are many ”on the shelf” networks, selecting or proposing a new appropriate network for a given data, signal or image processing, is still an open problem. In this presentation, we consider this problem using model based signal and image processing and inverse problems methods. We classify the methods in five classes, based on:
1- Explicite analytical solutions,
2- Transform domain decomposition,
3- Operator decomposition,
4- Unfolding the optimization algorithms,
5- Physics Informed NN methods (PINN).
Some examples of application in Acoustical imaging will be presented.
个人简介：
Distinguished Professor at Paris-Saclay University (Univ. Paris 11) France, Research Director of French National Research Center (CNRS). Pioneer and chairman of International Conference on Maximum Entropy and Bayesian Approaches (50 years); Top talent of Zhejiang Invited foreign-experts; Laureate of the Westlake Prize of Zhejiang for significate contribution of foreign experts; Laureate of the International scientific cooperation of Zhejiang.
He received the master and two PhD degrees from University of Paris 11 respectively in 1980, 1994 and 1998 respectively. His proposed Gaussian Porter image segmentation algorithm, fast Bayesian variational method, hyperparameter Bayesian inference method, etc., have been highly recognized by the international academic and industrial communities, and have been widely applied in the fields of non-destructive detection, mechanical fault diagnosis, medical image recognition, and industrial big data analysis. His methods and inventions have been directly adopted by Airbus, Thales, Dassault, CEA, etc. He has presided 31 projects (with 10 million euros funding), published over 300 papers, 2 monographs and 12 textbooks; He supervised 21 doctoral and 31 master's students.
