[PDF] Top 20 Music feature maps with convolutional neural networks for music genre classification
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Music feature maps with convolutional neural networks for music genre classification
... The classification task generally relies on supervised learning approaches such as K-Nearest Neighbor, Linear Discriminant Analysis, Adaboost, and Support Vector Machine (SVM), which have been widely ...case ... Voir le document complet
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Classification of Time-Series Images Using Deep Convolutional Neural Networks
... ABSTRACT Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw ...Time-Series ... Voir le document complet
9
Convolutional Neural Networks for Large-Scale Remote Sensing Image Classification
... Fully convolutional (16 × 16 output) Fig. 1: Convolutional neural network architectures ...64 feature maps of size 14 × ...outputs with a conditional random field, we argue that ... Voir le document complet
14
Fine-grained breast cancer classification with bilinear convolutional neural networks (BCNNS)
... Fine-grained classification can be applied to distinguish between the small inter-class and large intra-class variances in histopathological ...image classification differentiates between ... Voir le document complet
12
Linear and Deformable Image Registration with 3D Convolutional Neural Networks
... coordinates for each output voxel (G N ...produce feature maps with large value ranges which com- plicates ...case, for example, when Φ p d = 1 there is no change in the ... Voir le document complet
11
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation
... However, classification results among these studies are not directly comparable because they differ in terms of: i) sets of participants; ii) image preprocessing procedures, iii) cross-validation (CV) procedure ... Voir le document complet
69
Mental Workload Classification with fNIRS using Temporal Convolutional Networks
... Traditional classification techniques, such as SVM and KNN, require feature-selection including mean, standard deviation and kurtosis and preprocessing, which do not necessarily result in op- timum ... Voir le document complet
2
Classification of Time-Series Images Using Deep Convolutional Neural Networks
... model. For faster convergence, the stochastic gradient descent (SGD) is used for updating the ...the feature maps on input vector by passing from layer to layer until reaching the output (left ... Voir le document complet
9
Recurrent Neural Networks to Correct Satellite Image Classification Maps
... fully convolutional [6] version of Mnih’s network, since recent remote sensing work has shown the theoretical and practical advantages of this type of architecture [30], ...heat maps as classes ...performed ... Voir le document complet
11
Deep Background Subtraction with Scene-Specific Convolutional Neural Networks
... network for handwritten digit classifica- tion [ 12 ], except that subsampling is performed with max- pooling instead of averaging and hidden sigmoid units are replaced with rectified linear units ... Voir le document complet
5
High-resolution image classification with convolutional networks
... FCN with convolutional and subsampling layers (the topmost part of ...features maps is extracted from this network, which are naively upsampled to match the resolution of the higher- resolution ... Voir le document complet
5
High-Resolution Semantic Labeling with Convolutional Neural Networks
... images. For example, to deduce that a certain pixel belongs to a rooftop, it might not be enough to just consider its individual spectrum: we might need to observe a large patch around this pixel, taking into ... Voir le document complet
14
Learning Iterative Processes with Recurrent Neural Networks to Correct Satellite Image Classification Maps
... more with each other than with other objects ...classes. Convolutional neural networks (CNNs) [15] are receiv- ing an increasing attention, due to their ability to automati- cally ... Voir le document complet
10
Energy Efficient Techniques using FFT for Deep Convolutional Neural Networks
... Abstract—Deep convolutional neural networks (CNNs) has been developed for a wide range of applications such as image recognition, nature language processing, ...requirements for com- ... Voir le document complet
7
Controlled Vocabularies for Music Metadata
... together with its two OWL ontologies or SKOS vocabularies (via an URL or a file ...gether with information about the portions of the vocabu- laries covered by the alignment (Figure 2, ...line) for ... Voir le document complet
8
PAC: Privacy-Preserving Arrhythmia Classification with Neural Networks
... namely, with several heartbeat ...the classification of a single heartbeat may not be sufficient to diagnose the disease for a patient and the doctor may need to receive the classification of ... Voir le document complet
17
Open Music + Music Space = Open Space
... Dans notre exemple, des objets particuliers (objets «ostinato» ), simples, ont été conçus de manière à pouvoir effectuer les tests préliminaires plus simplement : ces objets sont munis [r] ... Voir le document complet
9
MAPS - A piano database for multipitch estimation and automatic transcription of music
... Thus, few databases are currently available (e.g. [2, 3, 4]). They are usually made up of isolated tones from various musical instruments and/or musical recordings. Then, when necessary, isolated tones may be added by ... Voir le document complet
12
Spatio-temporal convolutional neural networks for failure prediction
... matrix with the same depth as the original input, contrary to 3D convolution ...dimensions for a given feature and not on that of the different features between them- ...developed for video ... Voir le document complet
5
Convolutional neural networks for disaggregated population mapping using open data
... surface models”. However, availability of this type of data is very limited, restricting the geographical coverage of their application. Still, population density estimations have been carried out using satellite ... Voir le document complet
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