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Search results for: FEATURE WEIGHTED ATTENTION
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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Numbers, Please: Power- and Voltage-Related Indices in Control of a Turbine-Generator Set
PublicationThis paper discusses the proper selection and interpretation of aggregated control performance indices values mirroring the quality of electrical energy generation by a turbine-generator set cooperating with a power system. Typically, a set of basic/classical and individual indices is used in energy engineering to ensure the mirroring feature and is related to voltage, frequency and active or reactive power deviations from their...
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On Nonlinear Bending Study of a Piezo-Flexomagnetic Nanobeam Based on an Analytical-Numerical Solution
PublicationAmong various magneto-elastic phenomena, flexomagnetic (FM) coupling can be defined as a dependence between strain gradient and magnetic polarization and, contrariwise, elastic strain and magnetic field gradient. This feature is a higher-order one than piezomagnetic, which is the magnetic response to strain. At the nanoscale, where large strain gradients are expected, the FM effect is significant and could be even dominant. In...
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The effect of shear deformations' rotary inertia on the vibrating response of multi-physic composite beam-like actuators
PublicationIn consecutive studies on flexomagneticity (FM), this work investigates the flexomagnetic reaction of a vibrating squared multi-physic beam in finite dimensions. It is assumed that the bending and shear deformations cause rotary inertia. In the standard type of the Timoshenko beam the rotary inertia originated from shear deformations has been typically omitted. It means the rotary inertia resulting from shear deformation is a new...
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Multimodal Attention Stimulator
PublicationMultimodal attention stimulator was proposed and tested for improving auditory and visual attention, including pupils with developmental dyslexia. Results of the conducted experiments shown that the designed stimulator can be used in order to improve comprehension during reading tasks. The changes in the visual attention, observed in reading test results, translate into the overall reading performance.
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Weighted 2-sections and hypergraph reconstruction
PublicationIn the paper we introduce the notion of weighted 2-sections of hypergraphs with integer weights and study the following hypergraph reconstruction problems: (1) Given a weighted graph , is there a hypergraph H such that is its weighted 2-section? (2) Given a weighted 2-section , find a hypergraph H such that is its weighted 2-section. We show that (1) is NP-hard even if G is a complete graph or integer weights w does not exceed...
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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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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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Investigating Feature Spaces for Isolated Word Recognition
PublicationMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Chromatic cost coloring of weighted bipartite graphs
PublicationGiven a graph G and a sequence of color costs C, the Cost Coloring optimization problem consists in finding a coloring of G with the smallest total cost with respect to C. We present an analysis of this problem with respect to weighted bipartite graphs. We specify for which finite sequences of color costs the problem is NP-hard and we present an exact polynomial algorithm for the other finite sequences. These results are then extended...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Visual and Auditory Attention Stimulator for Assisting Pedagogical Therapy
PublicationVisual and auditory attention stimulator provides a system developed in order to improve reading skills using simultaneous presentation of text in its visual form and in transformed auditory form accompanied by related movie material. The described research employed 40 children at the age of 8 13 years having difficulties in learning of reading, who were diagnosed as having developmental dyslexia. It was shown that application...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Weighted Clustering for Bees Detection on Video Images
PublicationThis 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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Approximation Strategies for Generalized Binary Search in Weighted Trees
PublicationWe consider the following generalization of the binary search problem. A search strategy is required to locate an unknown target node t in a given tree T. Upon querying a node v of the tree, the strategy receives as a reply an indication of the connected component of T\{v} containing the target t. The cost of querying each node is given by a known non-negative weight function, and the considered objective is to minimize the total...
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A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublicationTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
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Weighted sequential classifier
PublicationZaproponowano wieloklasowe ważone kryterium Fishera i uzasadniono potrzebę jego wprowadzenia. Na bazie tego kryterium skonstruowano sekwencyjny algorytm uczenia klasyfikatora. Przedstawiono wyniki eksperymentów.
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Design of weighted PID controllers for control of the Stewart-Gough platform
PublicationStewart-Gough platform (SGP) is a popular parallel type manipulator that involves a 6 degrees of freedom (DOF) motion. In this paper, the process of mathematical modelling of SGP is presented. Two selected control algorithms that use PID controllers and weighted PID controllers are designed. Both control systems using these algorithms are implemented in MATLAB environment as well as on the actual SGP. Parameters of the controllers...
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Connected searching of weighted trees
PublicationW pracy pokazano, że problem spójnego przeszukiwania drzew ważonych jest silnie NP-zupełny. Problem pozostaje trudnym dla drzew z jednym wierzchołkiem o stopniu większym niż 2. Ponadto, przedstawiony został wielomianowy optymalny algorytm dla klasy drzew z ograniczonym stopniem.
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Connected searching of weighted trees
PublicationW artykule rozważamy problem spójnego przeszukiwania drzew obciążonych. Autorzy w [L. Barriere i inni, Capture of an intruder by mobile agents, SPAA'02 (2002) 200-209] twierdzą, że istnieje wielomianowy algorytm dla problemu obliczania optymalnej strategii przeszukiwania obciążonego drzewa. W niniejszej pracy pokazano, że problem ten jest obliczeniowo trudny nawet dla wierzchołkowo-obciążonych drzew (wagi krawędzi równe 1) oraz...
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Facial feature extraction from a monochromatic picture.
PublicationFace pose determination represents an important area of research in Human Machine Interaction. In this paper, I describe a new method of extracting facial feature locations from a single monochromatic monocular camera for the purpose of estimating and tracking the three dimensional pose of human face and eye-gaze direction.
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Facial Feature extraction from a monochromatic picture
PublicationFace pose determination represents an important area of research in Human Machine Interaction. In this paper, I describe a new method of extracting facial feature locations from a single monochromatic monocular camera for the purpose of estimating and tracking the three dimensional pose of human face and eye-gaze direction.
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Using similar classification tasks in feature extractor learning
PublicationThe article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.
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Tribological model of porous bearings with particular attention given to the lubricant lubricity
PublicationThe friction and wear problems, accompanying all the tribological systems, lead to reduced service life. In order to prevent such situation, it is necessary to maintain fluid friction, which improves durability of all friction nodes in a tribological system. In the paper, the tribological system consists of porous bearings and the model deals with their weakest spots - the oil outflow points in the porous wall. A kinetic model...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Weighted difference schemes for systems of quasilinear first order partial functional differential equations
PublicationThe paper deals with initial boundary value problems of the Dirichlet type for system of quasilinear functional differential equations. We investigate weighted difference methods for these problems. A complete convergence analysis of the considered difference methods is given. Nonlinear estimates of the Perron type with respect to functional variables for given functions are assumed. The proof of the stability of difference problems...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Visual Attention Distribution Based Assessment of User's Skill in Electronic Medical Record Navigation
PublicationCurrently, the most precise way of reflecting the skills level is an expert’s subjective assessment. In this paper we investigate the possibility of the use of eye tracking data for scalar quantitative and objective assessment of medical staff competency in EMR system navigation. According to the experiment conducted by Yarbus the observation process of particular features is associated with thinking. Moreover, eye tracking is...
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Approximate search strategies for weighted trees
PublicationW pracy podajemy 3-przybliżony algorytm dla problemu spójnego przeszukiwania drzew ważonych.
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Survivability weighted floodable length surfaces.
PublicationPraca przedstawia nowy typ krzywych grodziowych dla przedziałów poprzecznych, obliczanych dla zadanej wartości mnożnika si, traktowanego jako parametr. Krzywe takie są niezależne od aktualnego podziału grodziowego statku. Są niezmiernie użyteczne do otymalizowania podziału grodziowego w świetle probabilistycznych przepisów niezatapialności.
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
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IMPEDANCE MEASUREMENT MODULE FOR GAS SENSORS WITH TEMPERATURE CONDITIONING FEATURE
PublicationThe paper presents an impedance measurement module which is aimed for gas sensor. Sensor’s heater temperature conditioning and modulation feature is available in order to allow implementation of different techniques improving selectivity and sensitivity of gas sensors. The measurement module uses three-parameter sine-fitting technique for impedance measurement. To monitor sensor temperature, the resistance of the sensor’s heater...
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Low-Level Music Feature Vectors Embedded as Watermarks
PublicationIn this paper a method consisting in embedding low-level music feature vectors as watermarks into a musical signal is proposed. First, a review of some recent watermarking techniques and the main goals of development of digital watermarking research are provided. Then, a short overview of parameterization employed in the area of Music Information Retrieval is given. A methodology of non-blind watermarking applied to music-content...
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Response Feature Technology for High-Frequency Electronics. Optimization, Modeling, and Design Automation
PublicationThis book discusses response feature technology and its applications to modeling, optimization, and computer-aided design of high-frequency structures including antenna and microwave components. By exploring the specific structure of the system outputs, feature-based approaches facilitate simulation-driven design procedures, both in terms of improving their computational efficiency and reliability. These benefits are associated...
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Real-time facial feature tracking in poor quality thermal imagery
PublicationRecently, facial feature tracking systems have become more and more popular because of many possible use cases. Especially in medical applications location of the face and facial features are very useful. Many researches have presented methods to detect and track facial features in visible light. However, facial feature analysis in thermography may also be very advantageous. Some examples of using infrared imagery in medicine include...
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Weighted-Sum Approach to Health Care Optimization
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Non-standard binary weighted number systems
PublicationZdefiniowano szeroką klasę binarnych systemów wagowych. Wszystkie sa wzajemnie jednoznaczne ale mogą być zupełne lub niezupełne. Jeżeli wagi systemu są kolejnymi liczbami naturalnymi to system jest minimalny.Jesli wagi sa kolejnymi potęgami podstawy Z to system jest maksymalny. W przestrzeni między tymi systemami znajdują się inne systemy binarne. Kilka z nich przedstawiono w referacie.
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublicationThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublicationAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
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Neural network modelling of the influence of channelopathies on reflex visual attention
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublicationIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Rendezvous of heterogeneous mobile agents in edge-weighted networks
PublicationWe introduce a variant of the deterministic rendezvous problem for a pair of heterogeneous agents operating in an undirected graph, which differ in the time they require to traverse particular edges of the graph. Each agent knows the complete topology of the graph and the initial positions of both agents. The agent also knows its own traversal times for all of the edges of the graph, but is unaware of the corresponding traversal...
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Rendezvous of Heterogeneous Mobile Agents in Edge-Weighted Networks
PublicationWe introduce a variant of the deterministic rendezvous problem for a pair of heterogeneous agents operating in an undirected graph, which differ in the time they require to traverse particular edges of the graph. Each agent knows the complete topology of the graph and the initial positions of both agents. The agent also knows its own traversal times for all of the edges of the graph, but is unaware of the corresponding traversal...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Three-dimensional geographically weighted inverse regression (3GWR) model for satellite derived bathymetry using Sentinel-2 observations
PublicationCurrent trends of development of satellite derived bathymetry (SDB) models rely on applying calibration techniques including analytical approaches, neuro-fuzzy systems, regression optimization and others. In most of the cases, the SDB models are calibrated and verified for test sites, that provide favourable conditions for the remote derivation of bathymetry such as high water clarity, homogenous bottom type, low amount of sediment...
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Rapid Yield Estimation and Optimization of Microwave Structures Exploiting Feature-Based Statistical Analysis
PublicationIn this paper, we propose a simple, yet reliable methodology to expediteyield estimation and optimization of microwave structures. In our approach,the analysis of the entire response of the structure at hand (e.g., $S$-parameters asa function of frequency) is replaced by response surface modeling of suitablyselected feature points. On the one hand, this is sufficient to determinewhether a design satisfies given performance specifications....