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research_group:start [2020/05/06 20:57]
mpiekarski [Anomaly detection with the use of pre-trained CNN architectures]
research_group:start [2023/04/16 23:24] (current)
abrodzicki [Vehicle interior image segmentation]
Line 6: Line 6:
  
 ==== Deep neural networks in early detection of melanomas ==== ==== Deep neural networks in early detection of melanomas ====
-FIXME 
  
 +**Research goal:**\\
 +Extending the knowledge of melanoma classification by exploring areas such as:
 +  * Artifact removal
 +  * Thickness prediction
 +  * General anatomic sites localisation
 +  * Global pattern recognition
 +  * Differt approach to acral lesions
 +  * Confocal microscopy
 +
 +
 +People involved:
 +  * J. Jaworek-Korjakowska
 +  * A. Wójcicka
 +  * A. Brodzicki
 +  * F. Noworolnik
 +  * D. Kucharski
 ====  Computer-aided dermatopathology ==== ====  Computer-aided dermatopathology ====
  
Line 48: Line 63:
 To detect anomalies in multivariate diagnostic signals of the synchrotron control system by pre-trained CNN architectures. To detect anomalies in multivariate diagnostic signals of the synchrotron control system by pre-trained CNN architectures.
  
-SOLARIS National Synchrotron Radiation Centre is a research facility that provides high quality synchrotron light. To control such a complex system it is necessary to monitor signals from various devices and subsystems. Currently, just slow-changing anomalies are detected only by experienced operators but even those faults are recognized far too late. Anomaly detection prevents from financial loss, unplanned downtimes and in extreme cases cause damage. As artificial intelligence techniques including machine learning and deep neural networks have become state-of-the-art solutions for anomaly detection tasks which are one of the most challenging in data analysis, our team conducts research on the use of them for anomaly detection in multivariate diagnostic signals.+[[https://​synchrotron.uj.edu.pl|SOLARIS]] National Synchrotron Radiation Centre is a research facility that provides high quality synchrotron light. To control such a complex system it is necessary to monitor signals from various devices and subsystems. Anomaly detection prevents from financial loss, unplanned downtimes and in extreme cases cause damage. As artificial intelligence techniques including machine learning and deep neural networks have become state-of-the-art solutions for anomaly detection tasks which are one of the most challenging in data analysis, our team conducts research on the use of them for anomaly detection in multivariate diagnostic signals.
  
 The research topics include: The research topics include:
Line 58: Line 73:
   * M. Piekarski   * M. Piekarski
   * J. Jaworek-Korjakowska   * J. Jaworek-Korjakowska
-==== Detection and analysis of patterns ​(@asia: muszę dopracować ) ==== +==== Detection and analysis of patterns ====
-FIXME+
  
-==== Cell detection ​- Andrzej... ​====+==== Cell detection ====
  
-FIXME+To improve speed and quality of testing new drugs against Clostridium difficile infection, we developed an algorithm for automatic bacteria cytotoxicity classification. It was based on two kinds of fluorescence images - DAPI and GFP. We experimented with many different methods from classical image processing and machine learning algorithms to convolutional neural networks. This research was was conducted in cooperation with Stanford University.
  
 +The research topics include:
 +  * fluorescence images
 +  * image processing
 +  * sharing information from different images
 +  * convolutional neural networks
  
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * A. Brodzicki
  
 +==== Bacteria response clustering ====
 +
 +Newly opened project, in cooperation with Stanford University. The main idea is to analyse bacteria reaction in response to different serums.
 +
 +The research topics include:
 +  * data clustering
 +  * bacteria response analysis
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * A. Brodzicki
 +
 +==== Reconstructing images'​ missing areas with generative models ====
 +
 +The research topics include:
 +  * reconstruction
 +  * generative learning
 +  * GANs
 +  * autoencoders
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * D. Kucharski
 +
 +==== Vehicle interior image segmentation ====
 +
 +The research topics include:
 +  * dataset preparation
 +  * image classification
 +  * image segmentation
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * A. Kostuch
 +
 +==== Robotics ====
 +
 +The research covers the topic of reinforcement learning used for robotic arm optimal trajectory planning.
 +
 +Team members involved:
 +  * J. Jaworek-Korjakowska
 +  * M. Aleksandrowicz
  
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research_group/start.1588791472.txt.gz · Last modified: 2020/08/25 15:49 (external edit)