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Search results for: neural structure optimization
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?
PublicationDespite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected...
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Crystal structure and electronic structure of CePt2In7
PublicationWe report a corrected crystal structure for the CePt2In7 superconductor, refined from single crystal x-ray diffraction data. The corrected crystal structure shows a different Pt–In stacking along the c-direction in this layered material than was previously reported. In addition, all of the atomic sites are fully occupied with no evidence of atom site mixing, resolving a discrepancy between the observed high resistivity ratio of...
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Discrete Optimization
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Journal of Optimization
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OPTIMIZATION AND ENGINEERING
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Optimization Letters
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublicationIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Style Transfer for Detecting Vehicles with Thermal Camera
PublicationIn this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Efficiency comparison of selected endoscopic video analysis algorithms
PublicationIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Computationally Efficient Design Optimization of Compact Microwave and Antenna Structures
PublicationMiniaturization is one of the important concerns of contemporary wireless communication systems, especially regarding their passive microwave components, such as filters, couplers, power dividers, etc., as well as antennas. It is also very challenging, because adequate performance evaluation of such components requires full-wave electromagnetic (EM) simulation, which is computationally expensive. Although high-fidelity EM analysis...
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Zero-Pole Electromagnetic Optimization
PublicationA fast technique for the full-wave optimization of transmission or reflection properties of general linear timeinvariant high-frequency components is proposed. The method is based on the zeros and poles of the rational function representing the scattering parameters of the device being designed and it is the generalization of the technique developed for the design by optimization of microwave filters. The performance of the proposed...
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Multi-objective optimization of microextraction procedures
PublicationOptimization of extraction process requiresfinding acceptable conditions for many analytes and goodperformance in terms of process time or solvent consumption. These optimization criteria are oftencontradictory to each other, the performance of the system in given conditions is good for some criteriabut poor for others. Therefore, such problems require special assessment tools that allow to combinethese contradictory criteria into...
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ANN for human pose estimation in low resolution depth images
PublicationThe paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model is described. Then data preprocessing and normalization procedure, and DNN and MLP artificial neural networks architectures and training are presented. The robustness against camera distance and image noise is analysed....
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Comparison of selected electroencephalographic signal classification methods
PublicationA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublicationThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublicationThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublicationThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Multi-objective optimization of expensive electromagnetic simulation models
PublicationVast majority of practical engineering design problems require simultaneous handling of several criteria. For the sake of simplicity and through a priori preference articulation one can turn many design tasks into single-objective problems that can be handled using conventional numerical optimization routines. However, in some situations, acquiring comprehensive knowledge about the system at hand, in particular, about possible...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublicationThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Small Antenna Design Using Surrogate-Based Optimization
PublicationIn this work, design of small antennas using efficient numerical optimization is investigated. We exploit variable-fidelity electromagnetic (EM) simulations and the adaptively adjusted design specifications (AADS) technique. Combination of these methods allows us to simultaneously adjust multiple geometry parameters of the antenna structure of interest in a computationally feasible manner, leading to substantial reduction of the...
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Frontiers in Neural Circuits
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NEURAL COMPUTING & APPLICATIONS
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Neural Regeneration Research
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Neural Network World
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NEUROREHABILITATION AND NEURAL REPAIR
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NEURAL PROCESSING LETTERS
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Point cloud unification with optimization algorithm
PublicationTerrestrial laser scanning is a technology that enables to obtain three-dimensional data – an accurate representation of reality. During scanning not only desired objects are measured, but also a lot of additional elements. Therefore, unnecessary data is being removed, what has an impact on efficiency of point cloud processing. It can happen while single point clouds are displayed – user decides what he wants...
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Novel structure and design of compact UWB slot antenna
PublicationIn this paper, a novel structure of a compact UWB slot antenna is presented along with a simulation-driven design optimization algorithm for adjusting geometry parameters of the device. Our primary objective is to obtain small footprint of the structure while maintaining its acceptable electrical performance. It is achieved by introducing sufficiently large number of geometry degrees of freedom, including increased number of parameterized...
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Rapid design optimization of compact couplers using response features and adjoint sensitivities
PublicationA technique for rapid EM-driven design optimization of compact microwave couplers is presented. Our approach exploits response features and adjoint sensitivities and allows for low-cost design closure both in terms of performance enhancement and structure miniaturization. It is demonstrated using a compact rat-race coupler working at 1 GHz and compared to adjoint-based gradient optimization.
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Optimization of Energetic Train Cooperation
PublicationIn the article, possible ways of using energy recovered during regenerative braking of trains are presented. It is pointed out that the return of recovered electricity directly to the catenary and its use in the energy cooperation of vehicles can be a no-cost method (without additional infrastructure). The method of energy cooperation between trains and its main assumptions, that uses the law of conservation of energy, are described...
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A framework for accelerated optimization of antennas using design database and initial parameter set estimation
PublicationThe purpose of this paper is to exploit a database of pre-existing designs to accelerate parametric optimization of antenna structures is investigated. Design/methodology/approach The usefulness of pre-existing designs for rapid design of antennas is investigated. The proposed approach exploits the database existing antenna base designs to determine a good starting point for structure optimization and its response sensitivities....
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Intelligent Autonomous Robot Supporting Small Pets in Domestic Environment
PublicationIn this contribution, we present preliminary results of the student project aimed at the development of an intelligent autonomous robot supporting small pets in a domestic environment. The main task of this robot is to protect a freely moving small pets against accidental stepping on them by home residents. For this purpose, we have developed the mobile robot which follows a pet and makes an alarm signal when a human is approaching....
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublicationThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Music Mood Visualization Using Self-Organizing Maps
PublicationDue to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which...
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Analysis of Denoising Autoencoder Properties Through Misspelling Correction Task
PublicationThe paper analyzes some properties of denoising autoencoders using the problem of misspellings correction as an exemplary task. We evaluate the capacity of the network in its classical feed-forward form. We also propose a modification to the output layer of the net, which we called multi-softmax. Experiments show that the model trained with this output layer outperforms traditional network both in learning time and accuracy. We...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublicationTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Architektury klasyfikatorów obrazów
PublicationKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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Sylwester Kaczmarek dr hab. inż.
PeopleSylwester 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...
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Estimation of structural stiffness with the use of Particle Swarm Optimization
PublicationThe paper presents the theoretical background and four applications examples of the new method for the estimation of support stiffness coefficients of complex structures modelled discretely (e.g. with the use of the Finite Element Model (FEM) method based on the modified Particle Swarm Optimization (PSO) algorithm. In real-life cases, exact values of the supports’ stiffness coefficients may change for various reasons...
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Complex multidisciplinary optimization of turbine blading systems
PublicationThe paper describes the methods and results of direct optimization of turbine blading systems using a software package Opti_turb. The final shape of the blading is obtained from minimizing the objective function, which is the total energy loss of the stage, including the leaving energy. The current values of the objective function are found from 3D RANS computations (from a code FlowER) of geometries changed during the process...
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SIMULIA Optimization Day
EventsCentrum Informatyczne TASK oraz BUDSOFT zapraszają na seminarium "SIMULIA Optimization Day". Więcej informacji na stronie internetowej: https://task.gda.pl/nowosci/2019/simulia-optimization-day/
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Numerical optimization of planar antenna structures using trust-region algorithm with adaptively adjusted finite differences
Open Research DataThe dataset contains initial designs and optimization results for three planar structures that include quasi-patch antenna for WLAN applications, compact spline-parameterized monopole dedicated for ultra-wideband applications, as well as rectifier for energy harvesting with enhanced bandwidth. The numerical results for the first two structures are also...
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Structure and Environment
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...