Wyniki wyszukiwania dla: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES - MOST Wiedzy

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Wyniki wyszukiwania dla: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES

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Wyniki wyszukiwania dla: MULTI-TASK LEARNING, INSTRUMENT SEGMENTATION, VIDEO DEBLURRING, DENTAL MICROSCOPE, SPATIO-TEMPORAL FEATURES

  • Image Segmentation of MRI image for Brain Tumor Detection

    Publikacja

    - Rok 2020

    this research work presents a new technique for brain tumor detection by the combination of Watershed algorithm with Fuzzy K-means and Fuzzy C-means (KIFCM) clustering. The MATLAB based proposed simulation model is used to improve the computational simplicity, noise sensitivities, and accuracy rate of segmentation, detection and extraction from MR...

  • Atomic Force Microscope data post-processing algorithm for higher harmonics imaging

    Previous works have proved that higher harmonics topography imaging using atomic force microscope (AFM) can significantly enhanced its measurement capabilities. Integrated tools dedicated to most of microscopes allow to visualize the investigated surface only by one selected harmonic. Because of the different characteristics of a sample, scanning tip and the environment, appropriate harmonic selection is time consuming and requires...

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  • C2 NIWA Community-Segmentation Criteria and Building Brand Associations on the Example of a Selected Target Group

    Publikacja

    Every organization which offers products or services wishes to communicate with their customers in the most effective way. This kind of communication is based on proper selection of target groups, which are extracted in the process of market segmentation. That is way it is very important to ask the question to whom the message is to be directed and what kind of message we want to give. This article describes the selection criteria...

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  • BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising

    Denoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...

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  • Organochlorine pesticides in fish from the southern Baltic Sea: levels, bioaccumulation features and temporal trends during the 1995-2006 period

    Publikacja

    - MARINE POLLUTION BULLETIN - Rok 2008

    W próbkach pięciu gatunków ryb bałtyckich pobranych w latach 1995-2006 oznaczono zawartość heksachlorocykloheksanu (HCH), heksachlorobenzenu (HCB) oraz DDT i jego pochodnych. Dzięki zastosowaniu szeregu metod chemometrycznych a w szczególności analizy głównych składowych (PCA) zaobserwowano szereg istotnych zależności. Nie stwierdzono wpływu miejsca połowu na poziom analizowanych pestycydów w ciałach ryb. Zaobserwowano statystycznie...

  • Systematic approach to binary classification of images in video streams using shifting time windows

    in the paper, after pointing out of realistic recordings and classifications of their frames, we propose a new shifting time window approach for improving binary classifications. We consider image classification in tewo steps. in the first one the well known binary classification algorithms are used for each image separately. In the second step the results of the previous step mare analysed in relatively short sequences of consecutive...

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  • High-Speed Binary-to-Residue Converter Design Using 2-Bit Segmentation of the Input Word

    In this paper a new approach to the design of the high-speed binary-to-residue converter is proposed that allows the attaining of high pipelining rates by eliminating memories used in modulo m generators. The converter algorithm uses segmentation of the input binary word into 2-bit segments. The use and effects of the input word segmentation for the synthesis of converters for five-bit moduli are presented. For the number represented...

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  • Selection of Relevant Features for Text Classification with K-NN

    In this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...

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  • Training of Deep Learning Models Using Synthetic Datasets

    Publikacja

    - Rok 2022

    In order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...

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  • Image Classification Based on Video Segments

    Publikacja

    - Rok 2018

    In the dissertation a new method for improving the quality of classifications of images in video streams has been proposed and analyzed. In multiple fields concerning such a classification, the proposed algorithms focus on the analysis of single frames. This class of algorithms has been named OFA (One Frame Analyzed).In the dissertation, small segments of the video are considered and each image is analyzed in the context of its...

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  • Left Temporal Lobe Arachnoid Cyst Presenting with Symptoms of Psychosis

    Publikacja

    - Rok 2021

    This...

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  • System do prototypowania bezprzewodowych inteligentnych urządzeń monitoringu audio-video

    Publikacja

    - Rok 2013

    W komunikacie przedstawiono system prototypowania bezprzewodowych urządzeń do monitoringu audio-video. System bazuje na układach FPGA Virtex6 i wielu dodatkowych wspierających urządzeniach jak: szybka pamięć DDR3, mała kamera HD, mikrofon z konwerterem A/C, moduł radiowy WiFi, itp. Funkcjonalność systemu została szczegółowo opisana w komunikacie. System został zoptymalizowany do pracy pod kontrolą systemu operacyjnego Linux, zostały...

  • Design Elements of Affect Aware Video Games

    Publikacja

    - Rok 2015

    In this paper issues of design and development process of affect-aware video games are presented. Several important design aspects of such games are pointed out. A concept of a middleware framework is proposed that separates the development of affect-aware video games from emotion recognition algorithms and support from input sensors. Finally, two prototype affect-aware video games are presented that conform to the presented architecture...

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  • Weighted Clustering for Bees Detection on Video Images

    Publikacja

    This work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...

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  • Environmental failure of dental biomaterials

    W pracy przedstawiono problematykę związaną z zagadnieniem trwałości biomateriałów stomatologicznych. Scharakteryzowano kryteria doboru materiałów i na przykładzie koron stomatologicznych pokazano wyniki oceny prawidłowości doboru w oparciu o metodę elementów skończonych. Przedstawiono wyniki weryfikacji doświadczalnej i wskazano na możliwości wykorzystania tej metody do konstruowania odpornych na zniszczenie koron metalowo-ceramicznych.

  • Emotion Recognition for Affect Aware Video Games

    In this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented

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  • Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding

    Publikacja
    • Z. Waldman
    • L. Camarillo-Rodriguez
    • I. Chervenova
    • B. Berry
    • S. Shimamoto
    • B. Elahian
    • M. T. Kucewicz
    • C. Ganne
    • X. He
    • L. A. Davis... i 17 innych

    - EPILEPSY & BEHAVIOR - Rok 2018

    BACKGROUND: We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding. METHODS: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the...

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  • Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech

    Publikacja
    • D. Korzekwa
    • R. Barra-Chicote
    • B. Kostek
    • T. Drugman
    • M. Łajszczak

    - Rok 2019

    We present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...

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  • Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift

    While recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...

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  • Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms

    Publikacja

    - Rok 2014

    Implementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...

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  • Generalized Formulation of Response Features for Reliable Optimization of Antenna Input Characteristics

    Electromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models, are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure...

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  • POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2011

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  • Multi-Temporal Analysis of Changes of the Southern Part of the Baltic Sea Coast Using Aerial Remote Sensing Data

    Publikacja

    - Remote Sensing - Rok 2022

    Understanding processes that affect changes in the coastal zone and the ability to predict these processes in the future depends on the period for which detailed monitoring is carried out and on the type of coast. This paper analyzes a southern fragment of the Baltic coast (30 km), where there has been no anthropogenic impact (Slowinski National Park). The study was carried out covering a time interval of 65 years. Historic and...

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  • Urban scene semantic segmentation using the U-Net model

    Publikacja

    - Rok 2023

    Vision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...

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  • Nonlinear Modeling in Time Domain Numerical Analysis of Stringed Instrument Dynamics

    Publikacja

    Musical instruments are very various in terms of sound quality with their timbre shaped by materials and geometry. Materials' impact is commonly treated as dominant one by musicians, while it is unclear whether it is true or not. The research proposed in the study focuses on determining influence of both these factors on sound quality based on their impact on harmonic composition. Numerical approach has been chosen to allowed independent...

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  • Updating a hospital building. A task for innovation design

    Publikacja

    - Rok 2012

    Refurbishment of a hospital, especially located in a historical building, is a task that goes far beyond a standard framework of architectural practice. A concept of modularity in the architecture of the late nineteenth and early twentieth century was only just to happen, building system installations and technical equipment appeared as the simplest solutions. Inscribing complex functional solutions into such a space is an interesting...

  • Closed-loop stimulation of temporal cortex rescues functional networks and improves memory

    Publikacja
    • Y. Ezzyat
    • P. A. Wanda
    • D. F. Levy
    • A. Kadel
    • A. Aka
    • I. Pedisich
    • M. R. Sperling
    • A. Sharan
    • B. C. Lega
    • A. Burks... i 12 innych

    - Nature Communications - Rok 2018

    Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct...

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  • Dependence of Power Characteristics on Savonius Rotor Segmentation

    Publikacja
    • K. Doerffer
    • J. Telega
    • P. Doerffer
    • P. Hercel
    • A. Tomporowski

    - ENERGIES - Rok 2021

    Savonius rotors are large and heavy because they use drag force for propulsion. This leads to a larger investment in comparison to horizontal axis wind turbine (HAWT) rotors using lift forces. A simple construction of the Savonius rotor is preferred to reduce the production effort. Therefore, it is proposed here to use single-segment rotors of high elongation. Nevertheless, this rotor type must be compared with a multi-segment...

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  • A new multi-process collaborative architecture for time series classification

    Publikacja

    - KNOWLEDGE-BASED SYSTEMS - Rok 2021

    Time series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...

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  • Parallel Computations of Text Similarities for Categorization Task

    Publikacja

    - Rok 2013

    In this chapter we describe the approach to parallel implementation of similarities in high dimensional spaces. The similarities computation have been used for textual data categorization. A test datasets we create from Wikipedia articles that with their hyper references formed a graph used in our experiments. The similarities based on Euclidean distance and Cosine measure have been used to process the data using k-means algorithm....

  • Visual Features for Endoscopic Bleeding Detection

    Aims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...

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  • Lifelong Learning Idea in Architectural Education

    The recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...

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  • Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing

    Developing signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....

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  • Deep Learning

    Publikacja

    - Rok 2021

    Deep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...

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  • Objectivization of audio-video correlation assessment experiments

    Publikacja

    - Rok 2010

    The purpose of this paper is to present a new method of conducting an audio-visual correlation analysis employing a head-motion-free gaze tracking system. First, a review of related works in the domain of sound and vision correlation is presented. Then assumptions concerning audio-visual scene creation are shortly described. The objectivization process of carrying out correlation tests employing gaze-tracking system is outlined....

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  • Video of LEGO Bricks on Conveyor Belt Dataset Series

    Publikacja

    - Rok 2022

    The dataset series titled Video of LEGO bricks on conveyor belt is composed of 14 datasets containing video recordings of a moving white conveyor belt. The recordings were created using a smartphone camera in Full HD resolution. The dataset allows for the preparation of data for neural network training, and building of a LEGO sorting machine that can help builders to organise their collections.

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  • Bimodal deep learning model for subjectively enhanced emotion classification in films

    Publikacja

    - INFORMATION SCIENCES - Rok 2024

    This research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....

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  • Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation

    Publikacja

    - Rok 2023

    Machine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...

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  • Voltage Harmonics Transfer through Medium Voltage Instrument Transformers

    Publikacja

    Voltage transformers are widely used in power quality monitoring systems in medium and high voltage grids. This paper presents accuracy problems related to voltage harmonics transfer through instrument transformers. A simplified lumped-parameters wideband circuit model of the voltage transformer is proposed and verified by simulation and experimental investigations. A number of voltage transformers have been tested in the frequency...

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  • Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications

    Publikacja

    - The Learning Organization - Rok 2022

    Purpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...

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  • Selecting Features with SVM

    Publikacja

    A common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...

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  • MANAGING LEARNING PROCESS WITH E-LEARNING TOOL

    This article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework

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  • Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning

    Publikacja

    - Rok 2022

    My doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.

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  • Structural and Temporal Topic Models of Feedbacks on Service Quality – A Path to Theory Development?

    Publikacja

    - Rok 2020

    There is growing interest in applying computational methods in analysing large amount of data without sacrificing rigour in Information Systems research. In this paper, we demonstrate how the use of structural and temporal topic modelling can be employed to produce insights of both theoretical and practical importance from the analysis of textual comments on the quality of services in hospitals. As a first step, we revealed the...

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  • Divide and not forget: Ensemble of selectively trained experts in Continual Learning

    Publikacja
    • G. Rypeść
    • S. Cygert
    • V. Khan
    • T. Trzciński
    • B. Zieliński
    • B. Twardowski

    - Rok 2024

    Class-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...

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  • ISSUES OF CLASSIFICATION FUNCTION CONTINUITY IN ENDOSCOPIC VIDEO CLASSIFICATION

    Publikacja

    In the article a new way of analyzing the properties of feature vector functions (FVF) and classiers of images in a video stream is proposed. The general idea is based on focusing of the perceived continuity of the FVF and classier functions. Issues related to creating an exact mathematical model are discussed and a simplied solution is proposed. An exemplary algorithm is evaluated on three exemplary video sequences. The acquired...

  • A Method of MOS Evaluation for Video Based Services

    Publikacja

    - Rok 2016

    This paper deals with a method for QoE evaluation for the services transmitting large amount of data perceived by the end user in relatively short time periods, e.g. streaming video in mobile operator...

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  • Enterprise Gamification - Learning as a Side Effect of Competition

    Publikacja

    - Rok 2017

    Gmification in companies can be used for driving desired employees behaviour that are advantageous to their development and performance improvement. This paper presents tools acquired from online social networking services and game mechanisms to encourage managers to compete by providing extended statistics and user profiles features in e-learning system.

  • Facial features extraction for color, frontal images

    Publikacja

    - Rok 2011

    The problem of facial characteristic features extraction is discussed. Several methods of features extraction for color en--face photographs are discussed. The methods are based mainly on the colors features related to the specific regions of the human face. The usefulness of presented methods was tested on a database of en--face photographs consisting of 100 photographs.

  • Video analytics-based algorithm for monitoring egress from buildings

    A concept and a practical implementation of the algorithm for detecting of potentially dangerous situations related to crowding in passages is presented. An example of such a situation is a crush which may be caused by an obstructed pedestrian pathway. The surveillance video camera signal analysis performed in the online mode is employed in order to detect hold-ups near bottlenecks like doorways or staircases. The details of the...

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