Search results for: OPTICAL MICROSCOPY, BLOOD CELLS, BIOPHOTONICS, IMAGE ANALYSIS, CLASSIFICATION, EIGENFACES, NEURAL NETWORKS, DECISION SUPPORT, NANODIAMONDS, BIOIMAGING - Bridge of Knowledge

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Search results for: OPTICAL MICROSCOPY, BLOOD CELLS, BIOPHOTONICS, IMAGE ANALYSIS, CLASSIFICATION, EIGENFACES, NEURAL NETWORKS, DECISION SUPPORT, NANODIAMONDS, BIOIMAGING
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Search results for: OPTICAL MICROSCOPY, BLOOD CELLS, BIOPHOTONICS, IMAGE ANALYSIS, CLASSIFICATION, EIGENFACES, NEURAL NETWORKS, DECISION SUPPORT, NANODIAMONDS, BIOIMAGING

  • Computed aided system for separation and classification of the abnormal erythrocytes in human blood

    Publication

    - Year 2017

    The human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...

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  • MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS

    In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...

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  • Sylwester Kaczmarek dr hab. inż.

    Sylwester Kaczmarek received his M.Sc in electronics engineering, Ph.D. and D.Sc. in switching and teletraffic science from the Gdansk University of Technology, Gdansk, Poland, in 1972, 1981 and 1994, respectively. His research interests include: IP QoS and GMPLS and SDN networks, switching, QoS routing, teletraffic, multimedia services and quality of services. Currently, his research is focused on developing and applicability...

  • Deep neural networks for data analysis

    e-Learning Courses
    • K. Draszawka

    The aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...

  • Piotr Szczuko dr hab. inż.

    Piotr Szczuko received his M.Sc. degree in 2002. His thesis was dedicated to examination of correlation phenomena between perception of sound and vision for surround sound and digital image. He finished Ph.D. studies in 2007 and one year later completed a dissertation "Application of Fuzzy Rules in Computer Character Animation" that received award of Prime Minister of Poland. His interests include: processing of audio and video, computer...

  • 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...

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  • Selected Technical Issues of Deep Neural Networks for Image Classification Purposes

    In recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...

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  • Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support

    Publication

    - Year 2014

    In this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...

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  • DIFFRACTION PHASE MICROSCOPY FOR OBSERVATION ON RED BLOOD CELLS FLUCTUATION

    Nowadays there is quite huge need for more and more precise and effective fast diagnostics methods in hematology diseases. One of the most important blood components are erythrocytes – RBCs (Red Blood Cells). Due to their size they are easy to observe using microscopy. It is commonly known that the shape and lifetime of RBCs allows for early disease identification. Authors present special measurement system for RBCs fluctuations observation...

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  • Observation on red blood cells fluctuations by diffraction phase microscopy

    Publication

    Nowadays there is quite huge need for more and more precise and effective fast diagnostics methods in hematology diseases. One of the most important blood components are erythrocytes – Red Blood Cells (RBCs). Due to their size they are easy to observe using microscopy. It is commonly known that the shape and lifetime of RBCs allows for early disease identification. Authors present special measurement system for RBCs fluctuations...