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Search results for: VOCATIONAL TRAINING, INNOVATIVE TRAINING MASTER BSR, ERASMUS+
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Człowiek zanurzony w rzeczywistości wirtualnej na przykładzie Laboratorium Zanurzonej Wizualizacji Przestrzennej
PublicationArtykuł opisuje Laboratorium Zanurzonej Wizualizacji Przestrzennej (LZWP), które umożliwia swobodną podróż w czasie i przestrzeni. Jego podstawowym wyposażeniem jest jaskinia rzeczywistości wirtualnej, czyli pomieszczenie o ścianach, suficie i podłodze stanowiących ekrany projekcyjne, wyświetlające generowane komputerowo obrazy 3D, tworzące spójny widok jednej sceny. Człowiek znajdujący się w takiej jaskini jest zatem zanurzony...
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TeleCAD course online and evaluation procedure.
PublicationW artykule zaprezentowano system zarządzania nauczaniem na odległość -TeleCAD (Teleworkers Training for CAD Systems Users, projekt Leonardo da Vinci 1998-2001) i jego wykorzystanie w projekcie V Ramowy CURE 2003-2005). Przedstawiono również procedurę ewaluacyjną kursów na odległość na podstawie doświadczeń zdobytych podczas realizacji projektu Leonardo da Vinci EMDEL (European Model for Distance Education and Learning, 2001-2004).
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Endoscopic Videos Deinterlacing and On-Screen Text and Light Flashes Removal and Its Influence on Image Analysis Algorithms' Efficiency
PublicationIn this article, deinterlacing and removing on- screen text and light flashes methods on endoscopic video images are discussed. The research is intended to improve disease recognition algorithms' performance. In the article, four configurations of deinterlacing methods and another four configurations of text and flashes removal methods are described and examined. The efficiency of endoscopic video analysis algorithms is measured...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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From a Point Cloud to a 3D Model - an Exercise for Users of AutoCAD and Revit
PublicationThe paper presents a proposal of the topic of an exercise for students of building faculties as part of classes on 3D modelling. The task consists in creating a three-dimensional model based on the measurement obtained with the Leica P30 laser scanner. Due to the maximum number of points in the cloud in the presented programs, the output files must be properly cleared and reduced. The point cloud was pre-processed in Cyclone software....
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Previous Opinions is All You Need - Legal Information Retrieval System
PublicationWe present a system for retrieving the most relevant legal opinions to a given legal case or question. To this end, we checked several state-of-the-art neural language models. As a training and testing data, we use tens of thousands of legal cases as question-opinion pairs. Text data has been subjected to advanced pre-processing adapted to the specifics of the legal domain. We empirically chose the BERT-based HerBERT model to perform...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublicationThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublicationOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
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The experience of movement in orbital space architecture: A narrative of weightlessness
PublicationBased upon a combination of architectural theories, the knowledge of space environment, and psychology of isolated and confined environments, this qualitative research aims to study orbital space settlement in a way to get the built space congenial to the human experience of movement. In this sense, sensors, self-propulsion or mechanical actuators, the inhabitant’s mental and visual capacity for movement, as well as the represented...
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Social media for e-learning of citizens in smart city
PublicationThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Cost‐efficient performance‐driven modelling of multi‐band antennas by variable‐fidelity electromagnetic simulations and customized space mapping
PublicationElectromagnetic (EM) simulations have become an indispensable tool in the design of contemporary antennas. EM‐driven tasks, for example, parametric optimization, entail considerable computational efforts, which may be reduced by employing surrogate models. Yet, data‐driven modelling of antenna characteristics is largely hindered by the curse of dimensionality. This may be addressed using the recently reported domain‐confinement...
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The experience of movement in orbital space architecture: A narrative of weightlessness
PublicationBased upon a combination of architectural theories, the knowledge of space environment, and psychology of isolated and confined environments, this qualitative research aims to study orbital space settlement in a way to get the built space congenial to the human experience of movement. In this sense, sensors, self-propulsion or mechanical actuators, the inhabitant’s mental and visual capacity for movement, as well as the represented...
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Joanna Rymaszewska prof. dr hab. n. med.
PeopleCV Joanna Rymaszewska Wroclaw University of Science and Technology, Wroclaw, Poland +48 601 98 26 24, joanna.rymaszewska@pwr.edu.pl orcid.org/0000-0001-8985-3592 2023 → Professor of Wroclaw University of Science and Technology (WUST), Poland 2011 → 2023 Professor of Wroclaw Medical University (WMU), PL 2016 → 2022 Head of the Department of Psychiatry, Wroclaw Medical University 2016 → 2022 Head of the Clinic of Psychiatry,...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Anna Lis dr hab. inż.
PeopleAnna Lis has been the head of the Department of Management in Industry, Faculty of Economics and Management GUT since 2019. In 2005 she obtained Ph.D. degree in the field of Economic Sciences, in the discipline Management Sciences, 2019 – the degree of habilitated doctor in the field of Social Sciences, in the discipline of Management and Quality Studies. In the years 2004-2009 she was employed at the Faculty of Production Engineering...
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Tagged images with bees
Open Research DataImages taken from bee hive with tagged bees. The images are prepared for training yolo5 deep neural network (supplied with the data).
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Video of LEGO bricks on conveyor belt - flags and signs
Open Research DataThe set contains videos of LEGO bricks (flags and signs) moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final...
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Magdalena Gajewska prof. dr hab. inż.
PeopleMagdalena Gajewska (born June 1th 1968 in Gdańsk) in 1993 graduated Hydro-Engineering Faculty at Gdańsk University of Technology. At present she is an assistant professor in the Department of Water and Wastewater Technology at the Faculty of Civil and Environmental Engineering GUT. PhD (2001) and habilitation (2013) in the discipline of environmental engineering. In the 2016-2020 term, serves as Vice -dean for science. She...
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Auditory-visual attention stimulator
PublicationNew approach to lateralization irregularities formation was proposed. The emphasis is put on the relationship between visual and auditory attention stimulation. In this approach hearing is stimulated using time scale modified speech and sight is stimulated by rendering the text of the currently heard speech. Moreover, displayed text is modified using several techniques i.e. zooming, highlighting etc. In the experimental part of...
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Collaborative Data Acquisition and Learning Support
PublicationWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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Discussing daylight simulations in a proposal for online daylighting education.
PublicationThere is increasing interest concerning daylighting in the building sector. However, such knowledge is difficult to penetrate the curricula of architects and designers as existing educational programmes often do not provide sufficient training on BPS. This also leads to superficial use of daylight simulations. This paper presents a proposal for a needs-based education package on daylighting design, that mixes modular eLearning...
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Local Texture Pattern Selection for Efficient Face Recognition and Tracking
PublicationThis paper describes the research aimed at finding the optimal configuration of the face recognition algorithm based on local texture descriptors (binary and ternary patterns). Since the identification module was supposed to be a part of the face tracking system developed for interactive wearable computer, proper feature selection, allowing for real-time operation, became particularly important. Our experiments showed that it is...
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AITP - AI Thermal Pedestrians Dataset
PublicationEfficient pedestrian detection is a very important task in ensuring safety within road conditions, especially after sunset. One way to achieve this goal is to use thermal imaging in conjunction with deep learning methods and an annotated dataset for models training. In this work, such a dataset has been created by capturing thermal images of pedestrians in different weather and traffic conditions. All images were manually annotated...
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Evaluating Performance and Accuracy Improvements for Attention-OCR
PublicationIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
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AffecTube — Chrome extension for YouTube video affective annotations
PublicationThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...
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Otwarte zasoby edukacyjne - przegląd inicjatyw w Polsce i na świecie
PublicationOtwarte zasoby edukacyjne (OZE) to materiały szkoleniowe oraz narzędzia wspierające zarówno uczenie, jak i nauczanie. Zjawisko to nierozerwalnie łączy się z szerszym pojęciem otwartej edukacji (OE), które postuluje zniesienie barier w nauczaniu tak, aby uczący się mogli zdobywać wiedzę zgodnie ze swoimi potrzebami edukacyjno-szkoleniowymi. Celem artykułu jest zapoznanie czytelników z zagadnieniem otwartych zasobów edukacyjnych,...
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MOOCs in SP4CE - case studies (Strategic Partnership for Creativity and Entrepreneurship)
PublicationSP4CE stands for Strategic Partnership for Creativity and Entrepreneurship project which has been funded with support from the European Commission under the ERASMUS+ Programme in the period 1st September 2014 - 31st August 2017. The main purpose of SP4CE project is to design innovative e-learning tools for collaboration between students, enterprises and teachers. It concentrates on identifying users’ needs and supports the development...
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Melody Harmonization with Interpolated Probabilistic Models
PublicationMost melody harmonization systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric structure, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation....
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Ship Resistance Prediction with Artificial Neural Networks
PublicationThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublicationIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Nested Kriging with Variable Domain Thickness for Rapid Surrogate Modeling and Design Optimization of Antennas
PublicationDesign of modern antennas faces numerous difficulties, partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities (circular polarization, pattern diversity, band-notch operation), but also constraints imposed upon the physical size of the radiators. Conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise...
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Self-assessment of competencies of students and graduates participating in didactic projects – Case study
PublicationAim/purpose: the aim of this article is to examine the opinions of students and graduates of the faculty of economics of a technical university as regards their selfassessment of their preparation for entering the modern labour market. All the respondents participated during their studies in didactic projects aimed at improving their competencies taking into account the expectations of potential employers. Design/methodology/approach:...
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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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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Video of LEGO bricks on conveyor belt - slopes, arcs and rainbows
Open Research DataThe set contains videos of LEGO bricks (slopes, arcs and rainbows) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over...
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Employee benefits in comparision to the personal payroll fund in 2017-2019 on given example
Open Research DataIn modern employee relations, employers offer employees a whole range of benefits, which usually are required by the relevant regulations on the part of the employer, which serve to create appropriate working conditions.
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Video of LEGO bricks on conveyor belt - narrow plates
Open Research DataThe set contains videos of LEGO bricks (narrow plates) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final conveyor...
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Video of LEGO bricks on conveyor belt - narrow special plates
Open Research DataThe set contains videos of LEGO bricks (narrow special plates) moving on a white conveyor belt. The videos were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the...
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Video of LEGO bricks on conveyor belt - Technic pins
Open Research DataThe set contains videos of LEGO bricks (Technic pins) moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final conveyor...
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Tracing of dynamic objects in distributed interactive simulation systems
PublicationDistributed interactive simulation systems require integration of several areas of computer science and applied mathematics to enable each individual simulation object to visualize effectively dynamic states of other objects. Objects are unpredictable,i.e., controlled by their local operators, and are remote, i.e., must rely on some transmission media to visualize dynamic scene from their local perspectives. The paper...
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A measurement system for children endurance tests
PublicationThere are a lot of ethical problems concerning the use of invasive methods for the measurement of a child's body response to physical exercise and physical training. The alternative is are non-invasive methods like ergospirometry or NIRS. The article presents a measurement system dedicated for children endurance tests, composed of a few non-invasive measurement modules, including a temperature measurement module. Temperature is...
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Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych
PublicationThe aim of this article is to investigate whether separating music tracks at the pre-processing phase and extending feature vector by parameters related to the specific musical instruments that are characteristic for the given musical genre allow for efficient automatic musical genre classification in case of database containing thousands of music excerpts and a dozen of genres. Results of extensive experiments show that the approach...
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Fast multi-criterial statistical analysis and design optimization of compact microwave couplers
Publication—A rapid statistical analysis and yield estimation of compact microwave couplers involving multiple performance parameters has been presented. The analysis is realized using a fast surrogate model representing appropriate characteristic points of the coupler response. Because of less nonlinear dependence of the characteristic points on the structure geometry (compared to the original response, i.e., S-parameters vs. frequency),...
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Smart Modeling of Maritime Vessels
PublicationCurrently, the market offers many visualization tools available to graphic designers, engineers, managers and academics working on maritime environments. The practice of visualization involves making and manipulating images that convey novel phenomena and ideas. Visual communication, together with virtual reality environments, is an emerging and rapidly evolving discipline. It brings great advantage over written word or voice alone,...
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Recognition of hazardous acoustic events employing parallel processing on a supercomputing cluster . Rozpoznawanie niebezpiecznych zdarzeń dźwiękowych z wykorzystaniem równoległego przetwarzania na klastrze superkomputerowym
PublicationA method for automatic recognition of hazardous acoustic events operating on a super computing cluster is introduced. The methods employed for detecting and classifying the acoustic events are outlined. The evaluation of the recognition engine is provided: both on the training set and using real-life signals. The algorithms yield sufficient performance in practical conditions to be employed in security surveillance systems. The...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublicationDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...