Search
Didn't find any results in this catalog!
But we have some results in other catalogs.Filters
total: 1291
-
Catalog
- Publications 1084 available results
- Journals 7 available results
- Conferences 1 available results
- People 12 available results
- Projects 3 available results
- Laboratories 1 available results
- Research Teams 1 available results
- e-Learning Courses 48 available results
- Events 1 available results
- Open Research Data 133 available results
displaying 1000 best results Help
Search results for: 2D FEATURE SPACES
-
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...
-
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...
-
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...
-
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...
-
Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping 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....
-
Evolution of Edges and Porosity of Urban Blue Spaces: A Case Study of Gdańsk
PublicationCurrent waterfront studies focus mainly on a land-based perspective, failing to include the water side. Water is, however, not just a resource for port and industrial purposes and an edge to the waterfront; it is also a feature of the waterfront and the complex relation between water and city. Thus, the article suggests that water-land edges need to be re-contextualised, taking into consideration also their shape, functionality,...
-
Permeability of Waterfronts—Contemporary Approach in Designing Urban Blue Spaces
PublicationThe constant struggle with rising sea levels and flood hazards has resulted in the change of the paradigm in shaping urban waterfronts towards increasing their permeability and creation of urban blue spaces. The aim of the paper was to indicate a new approach in designing public spaces at the sea–land interface by presenting a comparative study of the design solutions used in case of the four selected case studies: the Sea Organs...
-
Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
-
2D Mathematical Model of the Commutator Sliding Contact of an Electrical Machine
PublicationW artykule przedstawiono model matematyczny 2D komutatorowego zestyku ślizgowego z wieloma stopniami swobody. W modelu uwzględniono zmienne wymuszenia działające na szczotkę. Wymuszenia te są wynikiem falistości wirującego komutatora. Szczotka została zamodelowana jako system wielu mas, elementów sprężystych i tłumików rozłożonych w kierunku stycznym i promieniowym. Zamodelowano wszystkie oddziaływania lepkosprężyste pomiędzy komutatorem...
-
Comparative molecular modelling of biologically active sterols
PublicationMembrane sterols are targets for a clinically important antifungal agent – amphotericin B. The relatively specific antifungal action of the drug is based on a stronger interaction of amphotericin B with fungal ergosterol than with mammalian cholesterol. Conformational space occupied by six sterols has been defined using the molecular dynamics method to establish if the conformational features correspond to the preferential interaction...