Wyszukiwarka
Filtry
wszystkich: 2180
-
Katalog
- Publikacje 1833 wyników po odfiltrowaniu
- Czasopisma 10 wyników po odfiltrowaniu
- Konferencje 10 wyników po odfiltrowaniu
- Osoby 49 wyników po odfiltrowaniu
- Projekty 3 wyników po odfiltrowaniu
- Kursy Online 26 wyników po odfiltrowaniu
- Wydarzenia 2 wyników po odfiltrowaniu
- Dane Badawcze 247 wyników po odfiltrowaniu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: multi-label classification
-
From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublikacjaIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
-
Multi-Label Classification for AIS Data Anomaly Detection Using Wavelet Transform
Publikacja -
A multi-label text message classification method designed for applications in call/contact centre systems
Publikacja -
Thresholding Strategies for Large Scale Multi-Label Text Classifier
PublikacjaThis article presents an overview of thresholding methods for labeling objects given a list of candidate classes’ scores. These methods are essential to multi-label classification tasks, especially when there are a lot of classes which are organized in a hierarchy. Presented techniques are evaluated using the state-of-the-art dedicated classifier on medium scale text corpora extracted from Wikipedia. Obtained results show that the...
-
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...
-
Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
-
Sylwester Kaczmarek dr hab. inż.
OsobySylwester Kaczmarek ukończył studia w 1972 roku jako mgr inż. Elektroniki, a doktorat i habilitację uzyskał z technik komutacyjnych i inżynierii ruchu telekomunikacyjnego w 1981 i 1994 roku na Politechnice Gdańskiej. Jego zainteresowania badawcze ukierunkowane są na: sieci IP QoS, sieci GMPLS, sieci SDN, komutację, ruting QoS, inżynierię ruchu telekomunikacyjnego, usługi multimedialne i jakość usług. Aktualnie jego badania skupiają...
-
Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
-
TF-IDF weighted bag-of-words preprocessed text documents from Simple English Wikipedia
Dane BadawczeThe SimpleWiki2K-scores dataset contains TF-IDF weighted bag-of-words preprocessed text documents (raw strings are not available) [feature matrix] and their multi-label assignments [label-matrix]. Label scores for each document are also provided for an enhanced multi-label KNN [1] and LEML [2] classifiers. The aim of the dataset is to establish a benchmark...
-
Differentiation Between Spirits According to Their Botanical Origin
PublikacjaAgricultural distillates are used for the production of spirit beverages. As more and more products with a specific botanical composition specified on the label are produced (e.g. rye vodkas, wheat vodkas and Polish Vodka, which cannot be produced with the addition of maize distillate), it is necessary to look for quicker and more accurate methods allowing the determination of botanical origin of alcoholic beverages and materials...
-
Zastosowanie elektronicznych zmysłów w analizie żywności. Zastosowanie elektronicznego języka w analizie żywności.
PublikacjaW dzisiejszych czasach konsumenci zwracają dużą uwagę na takie cechy żywności jak: zapach, smak i wygląd. Ze względu na to naukowcy od wielu lat podejmują próby naśladowania ludzkich narządów zmysłów za pomocą urządzeń określanych jako elektroniczne zmysły. Zaliczamy do nich elektroniczny nos i język oraz komputerowy system rozróżnienia barw i kształtów. Elektroniczny język znany również jako sztuczny język lub czujnik smaku,...
-
Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
-
Journal of Classification
Czasopisma -
Optical fiber aptasensor for label-free bacteria detection in small volumes
PublikacjaHighly sensitive devices for fast bacteria detection are sought to be developed with the task of quantifying the worldwide problem of pathogenic bacteria and thus helping to take control over spreading bacterial infections. This work concerns a sensing solution based on microcavity in-line Mach-Zehnder interferometer (μIMZI) induced in an optical fiber. Such a device exhibits ultrahigh sensitivity to refractive index changes...
-
Usługi ośrodków podregionalnych w Polsce
PublikacjaOśrodki podregionalne definiowane są jako miasta, w których skoncentrowane są takie usługi, które w Polsce mogą być w kilku miastach województwa, ale nie w każdym mieście powiatowym. Usługi zawsze miały tendencję do koncentracji, tworząc ośrodki różnych poziomów w hierarchicznej sieci osadniczej. Celem prezentowanych badań było: (1) określenie usług typowych dla poziomu podregionalnego; (2) rozpoznanie koncentracji tych usług,...
-
The EU Tyre Noise Label: The problem with measuring the noise level of only a few of all tyre variants
PublikacjaThe STEER project, described in another Inter-Noise 2022 paper, has evaluated the performance of the noise label of the European tyre label. The major finding was that uncertainties of the tyre/road noise measurements were higher than should be accepted. One of the worst uncertainty sources was found to be the common practice to measure only some tyres of all sizes or variants within a tyre line, to save money. Generally, only...
-
Physics augmented classification of fNIRS signals
PublikacjaBackground. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...
-
Emilia Miszewska dr inż.
OsobyEmilia Miszewska urodziła się w 1986 roku w Gdańsku. Ukończyła Szkołę Podstawową nr 17 w Gdańsku z klasami sportowymi o profilu pływanie oraz Liceum Sportowe nr 11 im. Janusza Kusocińskiego w Gdańsku. W 2005 roku rozpoczęła jednolite studia magisterskie na Wydziale Inżynierii Lądowej i Środowiska, które ukończyła w roku 2011, broniąc pracę dyplomową pt. „Analiza i opracowanie wytycznych zabezpieczenia pożarowego oraz planu...
-
Cataloging & Classification Quarterly
Czasopisma -
Vegetation Classification and Survey
Czasopisma -
Simultaneous optical and electrochemical label-free biosensing with ITO-coated lossy-mode resonance sensor
PublikacjaIn this work we discuss a new label-free biosensing device based on indium tin oxide (ITO) overlaid section of a multimode optical fiber fused silica core. The sensor has been used to optical measurements also simultaneously interrogated electrochemically (EC). Due to optimized thickness and optical properties of ITO film, a lossy-mode resonance (LMR) could be observed in the optical domain, where electrical properties of the film...
-
LEGO bricks for training classification network
Dane BadawczeThe data set contains images of 447 different classes of LEGO bricks used for training LEGO bricks classification network. The dataset contains two types of images: photos (10%) and renders (90%) aggregated into respective directories. Each directory (photos and renders) contains 447 directories labeled as the official brick type number. The images...
-
Seabed classification using multibeam echosounder
PublikacjaThe method of seabed identification and classification from multibeam sonar echoes is presented. The proposed approach is based on calculation of a set of parameters of an echo envelope, similarly as in seafloor classification using single beam echosounder. These parameters are extracted for each consecutive beam allowing the estimation of their dependence on the seafloor incident angle. The relation between seabed type and calculated...
-
Comparison of selected electroencephalographic signal classification methods
PublikacjaA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
-
Impact of optimization of ALS point cloud on classification
PublikacjaAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
-
A System for Heart Sounds Classification
PublikacjaThe future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...
-
Integration of protein tethering in a rapid and label-free SERS screening platform for drugs of abuse
PublikacjaSurface enhanced Raman spectroscopy (SERS) has emerged as a promising technique for the rapid and ultrasensitive detection of molecular species such as drugs of abuse in biofluids. Yet, it remains a significant challenge to create a viable screening tool for multiple drug classes, owing to the lack of affinity of certain species for the SERS substrate and to the matrix interference in complex media. Here we report a protein tethering...
-
Minimization of label usage in (G)MPLS networks
Publikacja -
Flood Classification in a Natural Wetland for Early Spring Conditions Using Various Polarimetric SAR Methods
PublikacjaAbstract--- One of the major limitations of remote sensing flood detection is the presence of vegetation. Our study focuses on a flood classification using Radarsat-2 Quad-Pol data in a natural floodplain during leafless, dry vegetation (early spring) state. We conducted a supervised classification of a data set composed of nine polarimetric decompositions and Shannon entropy followed by the predictors' importance estimation to...
-
The Hough transform in the classification process of inland ships
PublikacjaThis article presents an analysis of the possibilities of using image processing methods for feature extraction that allows kNN classification based on a ship’s image delivered from an on-water video surveillance system. The subject of the analysis is the Hough transform which enables the detection of straight lines in an image. The recognized straight lines and the information about them serve as features in the classification...
-
Using similar classification tasks in feature extractor learning
PublikacjaThe 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.
-
Selection of Relevant Features for Text Classification with K-NN
PublikacjaIn 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...
-
Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
-
Using multibeam echoes in seafloor characterisation and classification
PublikacjaThe method of seabed identification and classification from multibeam sonar echoes is presented. The proposed approach is based on calculation of a set of parameters of an echo envelope, similarly as in seafloor classification using single beam echosounder. These parameters are extracted for each consecutive beam allowing the estimation of their dependence on the seafloor incident angle. The relation between seabed type and calculated...
-
Functional fluorine-doped tin oxide coating for opto-electrochemical label-free biosensors
PublikacjaSensors operating in multiple domains, such as optical and electrochemical, offer properties making biosensing more effective than those working in a single domain. To combine such domains in one sensing device, materials offering a certain set of properties are required. Fluorine-doped tin oxide (FTO) thin film is discussed in this work as functional optically for guiding lossy modes and simultaneously electrochemically, i.e....
-
Image Classification Based on Video Segments
PublikacjaIn 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...
-
Clothes Detection and Classification Using Convolutional Neural Networks
PublikacjaIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
-
Basic Hand Gestures Classification Based on Surface Electromyography
PublikacjaThis paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...
-
Tailoring properties of indium tin oxide thin films for their work in both electrochemical and optical label-free sensing systems
PublikacjaThis work is devoted to the identification properties of indium tin oxide (ITO) thin films responsible for their possible application in combined optical and electrochemical label-free sensing systems offering enhanced functionalities. Since any post-processing would make it difficult to identify direct relation between deposition parameters and properties of the ITO films, especially when deposition on temperature-sensitive substrates...
-
Label‐free optical detection of cyclosporine in biological fluids
PublikacjaIn this paper, a spectroscopic method for determination of cyclosporine concentrations in biological fluids is presented. Blood plasma and hemoglobin solutions are chosen for the experiment. For various cyclosporine concentrations in blood plasma and hemoglobin, absorbance measurements in spectra range from 600 to 1100 nm are performed. The measurement results are analyzed by the use of a dedicated algorithm. The obtained data...
-
An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublikacjaOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
-
Automatic Classification of Polish Sign Language Words
PublikacjaIn the article we present the approach to automatic recognition of hand gestures using eGlove device. We present the research results of the system for detection and classification of static and dynamic words of Polish language. The results indicate the usage of eGlove allows to gain good recognition quality that additionally can be improved using additional data sources such as RGB cameras.
-
Using angular dependence of multibeam echo features in seabed classification
PublikacjaThe new approach to seabed classification based on processing multibeam sonar echoes is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry measurements or underwater object imaging, are also the promising tool in seafloor identification and classification, having several advantages over conventional single beam echosounders. The proposed seabed classification...
-
Advances in Data Analysis and Classification
Czasopisma -
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...
-
Magdalena Brzozowska-Woś dr hab. inż.
OsobyMagdalena Brzozowska-Woś jest absolwentką Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej (specjalność: systemy zarządzania). Jest również absolwentką Podyplomowego Studium Reklamy (Wydział Zarządzania i Ekonomii PG) oraz Podyplomowego Studium Public Relations (SWPS Uniwersytet Humanistycznospołeczny). W latach 2000-2003 współpracowała z Panoramą Internetu sp. z o. o. jako specjalista ds. marketingu. Pełniła również obowiązki...
-
Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
-
Classification of Music Genres by Means of Listening Tests and Decision Algorithms
PublikacjaThe paper compares the results of audio excerpt assignment to a music genre obtained in listening tests and classification by means of decision algorithms. A short review on music description employing music styles and genres is given. Then, assumptions of listening tests to be carried out along with an online survey for assigning audio samples to selected music genres are presented. A framework for music parametrization is created...
-
Endoscopic Video Classification with the Consideration of Temporal Patterns
PublikacjaThe article describes a novel approach to automatic recognition and classification of diseases in endoscopic videos. Current directions of research in this field are discussed. Most presented methods focus on processing single frames and do not take into consideration the temporal relationship between continuous classifications. Existing approaches that consider the temporal structure of an incoming frame sequence are focused on...
-
Behavioral state classification in epileptic brain using intracranial electrophysiology
PublikacjaOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...