{"title":"Fully Automatic Polyp Detection Based on a Novel U-Net Architecture and Morphological Post-Process","authors":"A. Tashk, J. Herp, E. Nadimi","doi":"10.1109/ICCAIRO47923.2019.00015","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00015","url":null,"abstract":"Colorectal lesions known as polyps are one of the diagnostic symptoms for colorectal disease. So, their accurate detection and localization based on a computer-aided diagnosis can assist colonists for prescribing more effective treatments. The computer vision and machine learning methods like pattern recognition and deep learning neural networks are the most popular strategies for automatic polyp detection purpose. The proposed approach in this paper is an innovative deep learning neural network. The proposed network has a novel U-Net architecture. The architecture of proposed network includes fully 3D layers which enable the network to be fed with multi or hyperspectral images or even video streams. Moreover, there is a dice prediction output layer. This type of output layer employs probabilistic approaches and benefits from more accurate prediction abilities. The proposed method is applied to international standard optical colonoscopy datasets known as CVC-ClinicDB, CVC-ColonDB and ETIS-Larib. The implementation and evaluation results demonstrate that the proposed U-Net outperforms other competitive methods for automatic polyp detection based on accuracy, precision, recall and F-Score criteria. The proposed method can assist experts and physicians to localize colonial polyps with more accuracy and speed. In addition, the proposed network can be used on live colonoscopy observations due to its high performance and fast operability.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126312786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On Soundness of Various Inference Rules for Vague Functional Dependencies","authors":"Dženan Gušić, Z. Šabanac, Sanela Nesimović","doi":"10.1109/ICCAIRO47923.2019.00036","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00036","url":null,"abstract":"In this paper we complement the most recent results on soundness of inference rules for new vague multivalued dependencies. Motivated by the fact that the inclusive and the augmentation rules are sound, we prove that: complementation, transitivity, replication, coalescence, union, pseudo-transitivity, decomposition, and mixed pseudo-transitivity rules are also sound. Our research relies on definitions of vague functional and vague multivalued dependencies based on appropriately selected similarity measures between vague values, vague sets, and tuples on sets of attributes.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131305679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discrete Gradation Surfaces Computation in Electrophotography","authors":"D. Tarasov, O. Milder","doi":"10.1109/ICCAIRO47923.2019.00043","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00043","url":null,"abstract":"Fine-tuning the reproduction of the initial colorants pure colors gradations is the basis of color reproduction in modern printing systems. Usually, tone reproduction curves are constructed by successively changing the tone of the basic dyes (CMYK). However, this approach does not take into account the effect of changes in the dyes shade when they overlap. As an alternative basis for color correction, we previously suggested using gradation trajectories, which are analogous to gradation curves in the CIE Lab space. We also proposed a discrete approach to computing them, using natural color discretization in digital printing devices. In this article, we propose to use three-dimensional gradation surfaces in the CIE Lab space as a mathematical model of double color overlays (RGB) and as a further development of the idea of gradation trajectories. The calculations use the mathematical apparatus of the differential geometry of spatial curves and surfaces. The color space metric is determined by the value of the CIE dE color difference. To simplify the application of the model, we also propose to carry out calculations in discrete form. In this case, color coordinates are considered as continuous functions of filling a discrete raster cell with two dyes. As gradation trajectories, we consider geodesic lines on the gradation surfaces of the corresponding double overlaps of dyes. For calculations we also used a discrete approach. Experimental verification was carried out using an electrophotographic printer.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126928465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Explicit Calculation of Reachable Sets to Illustrate Concepts in Optimal Control","authors":"Lilija Naiwert, K. Spindler","doi":"10.1109/ICCAIRO47923.2019.00022","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00022","url":null,"abstract":"This paper, which grew out of an ongoing project geared towards improvements in control education, provides an example of an autonomous two-dimensional control system which is simple enough to be completely analyzed analytically, but rich enough to exhibit interesting features. This example can be readily used in a course on optimal control to illustrate und visualize relevant control-theoretical concepts. We tried to present the material in a comprehensible and illustrative way which can be easily adapted for classroom use.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128584653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Effectiveness of the Piecewise Monotonic Approximation Method for the Peak Estimation of Noisy Univariate Spectra","authors":"I. C. Demetriou, Ioannis N. Perdikas","doi":"10.1109/ICCAIRO47923.2019.00020","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00020","url":null,"abstract":"We present examples of peak estimation to measurements of Raman, Infrared and NMR spectra by the piecewise monotonic data approximation method. The structural differences of these spectra, the complexity of the underlying physical laws and the error included in the measurements make this a good test of the effectiveness of the method. Precisely, if a number of monotonic sections of the data is required, then the optimal turning points and the least sum of squares of residuals are computed in quadratic complexity with respect to the number of data. This is a remarkable result because the problem may require an enormous number of combinations in order to find the optimal turning point positions. Our results exhibit some strengths and indicate certain advantages of the method. Therefore, they may be helpful to the development of new algorithms that are particularly suitable for peak estimation in spectroscopy calculations.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"66 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133008998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Compressing Convolutional Neural Networks by L0 Regularization","authors":"András Formanek, D. Hadhazi","doi":"10.1109/ICCAIRO47923.2019.00032","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00032","url":null,"abstract":"Convolutional Neural Networks have recently taken over the field of image processing, because they can handle complex non algorithmic problems with state-of-the-art results, based on precision and inference times. However, there are many environments (e.g. cell phones, IoT, embedded systems, etc.) and use-cases (e.g. pedestrian detection in autonomous driving assistant systems), where the hard real-time requirements can only be satisfied by efficient computational resource utilization. The general trend is training larger and more complex networks in order to achieve better accuracies and forcing these networks to be redundant (in order to increase their generalization ability). However, this produces networks that cannot be used in such scenarios. Pruning methods try to solve this problem by reducing the size of the trained neural networks. These methods eliminate the redundant computations after the training, which usually cause high drop in the accuracy. In this paper, we propose new regularization techniques, which induce the sparsity of the parameters during the training and in this way, the network can be efficiently pruned. From this viewpoint, we analyse and compare the effect of minimizing different norms of the weights (L1, L0) one by one and for groups of them (for kernels and channels). L1 regularization can be optimized by Gradient Descent, but this is not true for L0. The paper proposes a combination of Proximal Gradient Descent optimization and RMSProp method to solve the resulting optimization problem. Our results demonstrate that the proposed L0 minimization-based regularization methods outperform the L1 based ones, both in terms of sparsity of the resulting weight-matrices and the accuracy of the pruned network. Additionally, we demonstrate that the accuracy of deep neural networks can also be increased using the proposed sparsifying regularizations.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130831024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Developing a System Dynamics Model for Creating a Learning Sustainable Mobility Culture","authors":"George Papageorgiou, G. Demetriou","doi":"10.1109/ICCAIRO47923.2019.00037","DOIUrl":"https://doi.org/10.1109/ICCAIRO47923.2019.00037","url":null,"abstract":"This paper examines the concepts of learning and diffusion within the context of sustainable mobility and urban development. A System Dynamics (SD) model is proposed, which investigates plausible strategies that can change the mindsets of people towards active mobility. Treating the learning process as a diffusion control process for changing mindsets, is central to the development of the model. Specifically, awareness strategies are investigated as well as introducing Information and Communication Technology (ICT) in a computer simulated environment. The simulation results show that changing mindsets requires time in order to go through the process of knowledge, persuasion, decision, implementation and confirmation which is influenced by the formulated strategies. Carrying out a sensitivity analysis on the various parameters, it was revealed that for changing mindsets effectively, an awareness strategy should be reinforced with the use of an ICT strategy at specific time intervals, during the diffusion process. Optimization on minimizing the required time for developing a sustainable mobility culture is carried out. Such results would be of great use for policy makers interested to promote sustainable mobility such as walking, since their decisions can be tested prior to implementation.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114553267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Filters in Michálek's Fuzzy Topological Spaces","authors":"F. Lupiáñez","doi":"10.1109/iccairo47923.2019.00016","DOIUrl":"https://doi.org/10.1109/iccairo47923.2019.00016","url":null,"abstract":"The aim of this paper is to study some properties of filters in Michálek's fuzzy topological spaces, which are quite different of the classic properties of fuzzy topology. That continues a previous paper of this author.","PeriodicalId":297342,"journal":{"name":"2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116620506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}