dr hab. inż. Michał Grochowski
- Head of Department at Katedra Inteligentnych Systemów Sterowania i Wspomagania Decyzji
- Professor at Katedra Inteligentnych Systemów Sterowania i Wspomagania Decyzji
- Katedra Inteligentnych Systemów Sterowania i Wspomagania Decyzji
- Faculty of Electrical and Control Engineering
Budynek Wydz. Elektr.
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Head of Department
Data augmentation for improving deep learning in image classification problem
These days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
Hierarchical predictive control of integrated wastewater treatment systems
The paper proposes an approach to designing the control structure and algorithms for optimising control of integrated wastewater treatment plant-sewer systems (IWWTS) under a full range of disturbance inputs. The optimised control of IWWTS allows for significant cost savings, fulfilling the effluent discharge limits over a long period and maintaining the system in sustainable operation. Due to the specific features of a wastewater...
Deep neural networks approach to skin lesions classification — A comparative analysis
The paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
Obtained scientific degrees/titles
Obtained science degreedr hab. inż. Automation, electronics, electrical engineering and space technologies (Engineering and Technology)
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