Sökning: "Environmental Sound Classification"
Visar resultat 1 - 5 av 9 uppsatser innehållade orden Environmental Sound Classification.
1. Bjälklag av limträdäck : En jämförelse av handberäkningar och databaserat verktyg för dimensionering av bjälklag i kontor och lager med hänsyn till svikt och vibration
M1-uppsats, Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)Sammanfattning : Det ökade kravet på minskad klimatpåverkan vid upprättande av nybyggnationer leder till ett större fokus på miljömedvetna materialval. Vägen till ett mer hållbart byggande kan vara att ersätta koldioxidbelastade material som betong med en förnyelsebar resurs som trä. LÄS MER
2. Compare Accuracy of Alternative Methods for Sound Classification on Environmental Sounds of Similar Characteristics
Master-uppsats, Stockholms universitet/Statistiska institutionenSammanfattning : Artificial neural networks have in the last decade been a vital tool in image recognition, signal processing and speech recognition. Because of these networks' ability to be highly flexible, they suit a vast amount of different data. This flexible attribute is very sought for within the field of environmental sound classification. LÄS MER
3. Laminated veneer lumber floor : An evaluation of performance
Master-uppsats, KTH/Bro- och stålbyggnadSammanfattning : The ongoing climate change has become a very discussed and accurate topic. A fifth of the Swedishemissions of greenhouse gases originate from buildings (Boverket, n.d). LÄS MER
4. An IoT Solution for Urban Noise Identification in Smart Cities : Noise Measurement and Classification
Master-uppsats, Linnéuniversitetet/Institutionen för fysik och elektroteknik (IFE)Sammanfattning : Noise is defined as any undesired sound. Urban noise and its effect on citizens area significant environmental problem, and the increasing level of noise has become a critical problem in some cities. Fortunately, noise pollution can be mitigated by better planning of urban areas or controlled by administrative regulations. LÄS MER
5. Audio representation for environmental sound classification using convolutional neural networks
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : A convolutional neural network (CNN) training framework is described and implemented. The framework is used to train and evaluate an audio classification system, focused on evaluating differences in audio representation. The dataset used is ESC-50, containing 50 different classes of audio. LÄS MER