Genre classification
46 papers with code • 2 benchmarks • 6 datasets
Genre classification is the process of grouping objects together based on defined similarities such as shape, pixel, location, or intensity.
Most implemented papers
Gated Multimodal Units for Information Fusion
The Gated Multimodal Unit (GMU) model is intended to be used as an internal unit in a neural network architecture whose purpose is to find an intermediate representation based on a combination of data from different modalities.
Judging a Book By its Cover
Book covers communicate information to potential readers, but can that same information be learned by computers?
Music Genre Classification with Paralleling Recurrent Convolutional Neural Network
Deep learning has been demonstrated its effectiveness and efficiency in music genre classification.
Convolutional Neural Network Achieves Human-level Accuracy in Music Genre Classification
Here, we propose a new method that combines knowledge of human perception study in music genre classification and the neurophysiology of the auditory system.
Texture Selection for Automatic Music Genre Classification
In this paper, we evaluate the impact of frame selection on automatic music genre classification in a bag of frames scenario.
On large-scale genre classification in symbolically encoded music by automatic identification of repeating patterns
The importance of repetitions in music is well-known.
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training
Inspired by the success of pre-training models in natural language processing, in this paper, we develop MusicBERT, a large-scale pre-trained model for music understanding.
Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features
Along with the evolution of music technology, a large number of styles, or "subgenres," of Electronic Dance Music(EDM) have emerged in recent years.
Hierarchical quantum circuit representations for neural architecture search
The QCNN is a circuit model inspired by the architecture of Convolutional Neural Networks (CNNs).
Explaining Deep Convolutional Neural Networks on Music Classification
Deep convolutional neural networks (CNNs) have been actively adopted in the field of music information retrieval, e. g. genre classification, mood detection, and chord recognition.