Filtry
wszystkich: 712
Wyniki wyszukiwania dla: neural network
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Multimodal Approach For Polysensory Stimulation And Diagnosis Of Subjects With Severe Communication Disorders
Publikacjais evaluated on 9 patients, data analysis methods are described, and experiments of correlating Glasgow Coma Scale with extracted features describing subjects performance in therapeutic exercises exploiting EEG and eyetracker are presented. Performance metrics are proposed, and k-means clusters used to define concepts for mental states related to EEG and eyetracking activity. Finally, it is shown that the strongest correlations...
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Comparing the Effectiveness of ANNs and SVMs in Forecasting the Impact of Traffic-Induced Vibrations on Building
PublikacjaTraffic - induced vibrations may cause damage to structural elements and may even lead to structural collapse. The aim of the article is to compare the effectiveness of algorithms in forecasting the impact of vibrations on buildings using the Machine Learning (ML) methods. The paper presents two alternative approaches by using Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Factors that may affect traffic-induced...
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Rotor Blade Geometry Optimisation in Kaplan Turbine
PublikacjaThe paper presents the description of method and results of rotor blade shape optimisation. The rotor blading constitutes a part ofturbine flow path. Optimisation consists in selection of the shape that minimises ratio of polytrophic loss. Shape of the blade isdefined by the mean camber line and thickness of the airfoil. Thickness is distributed around the camber line based on the ratio ofdistribution. Global optimisation was done...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Budowa modelu prognostycznego dla farmy wiatrowej w środowisku MATLAB
PublikacjaLiberalizacja rynku energii elektrycznej sprawiła, że branża elektroenergetyczna przechodzi obecnie dynamiczny rozwój różnych jej obszarów (aspektów). Jednym z aspektów jest prognozowanie mocy jednostek wytwórczych źródeł wiatrowych. W prognozowaniu wykorzystuje się różnego rodzaju narzędzia matematyczne. Autor niniejszej publikacji poświęcił szczególną uwagę sztucznym sieciom neuronowym. Za pomocą modeli neuronowych istnieje możliwość...
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Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublikacjaThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine 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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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublikacjaLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Dane BadawczeMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublikacjaRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
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Automatic Rhythm Retrieval from Musical Files
PublikacjaThis paper presents a comparison of the effectiveness of two computational intelligence approaches applied to the task of retrieving rhythmic structure from musical files. The method proposed by the authors of this paper generates rhythmic levels first, and then uses these levels to compose rhythmic hypotheses. Three phases: creating periods, creating simplified hypotheses and creating full hypotheses are examined within this study....
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The Neural Knowledge DNA Based Smart Internet of Things
PublikacjaABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublikacjaThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaThe 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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Early warning models against bankruptcy risk for Central European and Latin American enterprises
PublikacjaThis article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warningmodels for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Surface EMG-based signal acquisition for decoding hand movements
Dane BadawczeBiosignal processing plays a crucial role in modern hand prosthetics. The challenge is to restore functionality of a lost limb based on the signals acquired from the surface of the stump. The number of sensors (emg channels) used for signal acquisition influence the quality of a prosthetic hand. Modern algorithms (including neural networks) can significantly...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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MobileNet family tailored for Raspberry Pi
PublikacjaWith the advances in systems-on-a-chip technologies, there is a growing demand to deploy intelligent vision systems on low-cost microcomputers. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity of contemporary convolutional neural networks (CNNs). The state-of-the-art lightweight CNN is MobileNetV3. However, it was designed to achieve a good trade-off between...
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Consciousness Study of Subjects with Unresponsive Wakefulness Syndrome Employing Multimodal Interfaces
PublikacjaThe paper presents a novel multimodal-based methodology for consciousness study of individuals with unresponsive wakefulness syndrome. Two interfaces were employed in the experiments: eye gaze tracking system – CyberEye developed at the Multimedia Systems Department, and EEG device with electrode placement in the international 10-20 standard. It was a pilot study for checking if it is possible to determine objective methods based...
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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublikacjaLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublikacjaThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublikacjaThe automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...
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Performance Analysis of the OpenCL Environment on Mobile Platforms
PublikacjaToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
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Improving Accuracy of Respiratory Rate Estimation by Restoring High Resolution Features With Transformers and Recursive Convolutional Models
PublikacjaNon-contact evaluation of vital signs has been becoming increasingly important, especially in light of the COVID- 19 pandemic, which is causing the whole world to examine people’s interactions in public places at a scale never seen before. However, evaluating one’s vital signs can be a relatively complex procedure, which requires both time and physical contact between examiner and examinee. These re- quirements limit the number...
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Multi-objective optimization of tool wear, surface roughness, and material removal rate in finishing honing processes using adaptive neural fuzzy inference systems
PublikacjaHoning processes are usually employed to manufacture combustion engine cylinders and hydraulic cylinders. A crosshatch pattern is obtained that favors the oil flow. In this paper, Adaptive Neural Fuzzy Inference System (ANFIS) models were obtained for tool wear, average roughness Ra, cylindricity and material removal rate in finish honing processes. In addition, multi-objective optimization with the desirability function method...
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Power of the low alpha brainwaves in the mental imagery experiment in sport: the "Your Home Venue" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the low alpha brainwaves in the mental imagery experiment in sport: the "Slow Start" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with...
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Power of the SMR brainwaves in the mental imagery experiment in sport: the "Start in High Level Championship" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with...
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Power of the low alpha brainwaves in the mental imagery experiment in sport: the "Successful Competition" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the high alpha brainwaves in the mental imagery experiment in sport: the "Your Home Venue" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the SMR brainwaves in the mental imagery experiment in sport: the "Fitness Activity" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with...
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Power of the SMR brainwaves in the mental imagery experiment in sport: the "Slow Start" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with...
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Power of the high alpha brainwaves in the mental imagery experiment in sport: the "Training Session" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the SMR brainwaves in the mental imagery experiment in sport: the "Successful Competition" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the SMR brainwaves in the mental imagery experiment in sport: the "Training Session" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the low alpha brainwaves in the mental imagery experiment in sport: the "Training Session" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the high alpha brainwaves in the mental imagery experiment in sport: the "Slow Start" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with...
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Power of the high alpha brainwaves in the mental imagery experiment in sport: the "Successful Competition" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the SMR brainwaves in the mental imagery experiment in sport: the "Your Home Venue" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The study's main aim was to examine the cortical correlations of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with the...
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Power of the high alpha brainwaves in the mental imagery experiment in sport: the "Fitness Activity" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with...
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Power of the low alpha brainwaves in the mental imagery experiment in sport: the "Fitness Activity" scenario.
Dane BadawczeThe data were collected to perform research on the neural oscillation during mental imagery in sport. The main aim of the study was to examine the cortical correlates of imagery depending on instructional modality (guided vs self-produced) using various sport-related scripts. The research was based on the EEG signals recorded during the session with...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublikacjaThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublikacjaThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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A new multi-process collaborative architecture for time series classification
PublikacjaTime 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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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublikacjaThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Online sound restoration system for digital library applications
PublikacjaAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...