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wszystkich: 821
Wyniki wyszukiwania dla: NEURAL%20STRUCTURE%20OPTIMIZATION
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublikacjaVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublikacjaThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...
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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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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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Photos of LEGO bricks
Dane BadawczeRandom photos of the following LEGO bricks: 2419, 2450, 3022, 3031, 4070, 30357, 41682, 44570, 47998, 52107, 54383, 54384, 64799, 87609, 93274, 99206, 99781. The bricks were placed on a white sheet of paper, the photos were taken by hand, using Huawei P20 PRO camera positioned above the bricks. The photos were taken with and without flashlight. The...
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublikacjaW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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Mask Detection and Classification in Thermal Face Images
PublikacjaFace masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Prognozirovanie svojstv betonov s pomoŝ'û iskusstvennyh nejronovyh setej
PublikacjaObserwacje mózgu ludzkiego oraz podstawowych komórek z jakich się składa (neuronów), doprowadziły do prób modelowania niedużych układów połączonych neuronów. Układy te, zwane w literaturze jako sieci neuronowe lub sieci neuropodobne (ang. neural network) wykazują pewne cechy zbliżone do cech mózgu. Są nimi np. zdolność uczenia i kojarzenia. Choć znany obecnie model matematyczny neuronu jest dość skomplikowany, to zachęcające wyniki...
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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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Special techniques and future perspectives: Simultaneous macro- and micro-electrode recordings
PublikacjaThere are many approaches to studying the inner workings of the brain and its highly interconnected circuits. One can look at the global activity in different brain structures using non-invasive technologies like positron emission tomography (PET) or functional magnetic resonance imaging (fMRI), which measure physiological changes, e.g. in the glucose uptake or blood flow. These can be very effectively used to localize active patches...
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How to Sort Them? A Network for LEGO Bricks Classification
PublikacjaLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Equal Baseline Camera Array—Calibration, Testbed and Applications
PublikacjaThis paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative...
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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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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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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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Novel analytical method for detection of orange juice adulteration based on ultra-fast gas chromatography
PublikacjaThe food authenticity assessment is an increasingly important issue in food quality and safety. The application of an electronic nose based on ultra-fast gas chromatography technique enables rapid analysis of the volatile compounds from food samples. Due to the fact that this technique provides chemical profiling of natural products, it can be a powerful tool for authentication in combination with chemometrics. In this article,...
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Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublikacjaAbstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublikacjaIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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Vehicle Detection with Self-Training for Adaptative Video Processing Embedded Platform
PublikacjaTraffic monitoring from closed-circuit television (CCTV) cameras on embedded systems is the subject of the performed experiments. Solving this problem encounters difficulties related to the hardware limitations, and possible camera placement in various positions which affects the system performance. To satisfy the hardware requirements, vehicle detection is performed using a lightweight Convolutional Neural Network (CNN), named...
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Limited selectivity of amperometric gas sensors operating in multicomponent gas mixtures and methods of selectivity improvement
PublikacjaIn recent years, smog and poor air quality have became a growing environmental problem. There is a need to continuously monitor the quality of the air. The lack of selectivity is one of the most important problems limiting the use of gas sensors for this purpose. In this study, the selectivity of six amperometric gas sensors is investigated. First, the sensors were calibrated in order to find a correlation between the concentration...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublikacjaW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wyko-rzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Prognozowanie wpływu drgań komunikacyjnych na budynki mieszkalne za pomocą sztucznych sieci neuronowych i maszyn wektorów wspierających
PublikacjaDrgania komunikacyjne mogą stanowić duże obciążenie eksploatacyjne budynku, powodując zarysowania i spękania tynków, odpadanie wypraw, zarysowania konstrukcji, pękanie elementów konstrukcji lub nawet zawalenie się budynku. Pomiary drgań na rzeczywistych konstrukcjach są pracochłonne i kosztowne, a co ważne nie w każdym przypadku są one uzasadnione. Celem pracy jest analiza autorskiego algorytmu, dzięki któremu z dużym prawdopodobieństwem...
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Wykorzystanie sztucznych sieci neuronowych do wykrywania i rozpoznawania tablic rejestracyjnych na zdjęciach pojazdów
PublikacjaW artykule przedstawiono koncepcję algorytmu wykrywania i rozpoznawania tablic rejestracyjnych (AWiRTR) na obrazach cyfrowych pojazdów. Detekcja i lokalizacja tablic rejestracyjnych oraz wyodrębnienie z obrazu tablicy rejestracyjnej poszczególnych znaków odbywa się z wykorzystaniem podstawowych technik przetwarzania obrazu (przekształcenia morfologiczne, wykrywanie krawędzi) jak i podstawowych danych statystycznych obiektów wykrytych...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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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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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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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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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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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublikacjaDeveloping 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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LONG-TERM RISK CLASS MIGRATIONS OF NON-BANKRUPT AND BANKRUPT ENTERPRISES
PublikacjaThis paper investigates how the process of going bankrupt can be recognized much earlier by enterprises than by traditional forecasting models. The presented studies focus on the assessment of credit risk classes and on determination of the differences in risk class migrations between non-bankrupt enterprises and future insolvent firms. For this purpose, the author has developed a model of a Kohonen artificial neural network to...
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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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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...