A review of novelty detection
Novelty detection is the task of classifying test data that differ in some respect from the data
that are available during training. This may be seen as “one-class classification”, in which a …
that are available during training. This may be seen as “one-class classification”, in which a …
A survey of emergencies management systems in smart cities
The rapid urbanization process in the last century has deeply changed the way we live and
interact with each other. As most people now live in urban areas, cities are experiencing …
interact with each other. As most people now live in urban areas, cities are experiencing …
Convolutional prototype network for open set recognition
Despite the success of convolutional neural network (CNN) in conventional closed-set
recognition (CSR), it still lacks robustness for dealing with unknowns (those out of known …
recognition (CSR), it still lacks robustness for dealing with unknowns (those out of known …
Description and discussion on DCASE2020 challenge task2: Unsupervised anomalous sound detection for machine condition monitoring
In this paper, we present the task description and discuss the results of the DCASE 2020
Challenge Task 2: Unsupervised Detection of Anomalous Sounds for Machine Condition …
Challenge Task 2: Unsupervised Detection of Anomalous Sounds for Machine Condition …
ToyADMOS: A dataset of miniature-machine operating sounds for anomalous sound detection
Y Koizumi, S Saito, H Uematsu… - 2019 IEEE Workshop …, 2019 - ieeexplore.ieee.org
This paper introduces a new dataset called" ToyADMOS" designed for anomaly detection in
machine operating sounds (ADMOS). To the best our knowledge, no large-scale datasets …
machine operating sounds (ADMOS). To the best our knowledge, no large-scale datasets …
Unsupervised detection of anomalous sound based on deep learning and the neyman–pearson lemma
Y Koizumi, S Saito, H Uematsu… - … on Audio, Speech …, 2018 - ieeexplore.ieee.org
This paper proposes a novel optimization principle and its implementation for unsupervised
anomaly detection in sound (ADS) using an autoencoder (AE). The goal of the unsupervised …
anomaly detection in sound (ADS) using an autoencoder (AE). The goal of the unsupervised …
A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks
Acoustic novelty detection aims at identifying abnormal/novel acoustic signals which differ
from the reference/normal data that the system was trained with. In this paper we present a …
from the reference/normal data that the system was trained with. In this paper we present a …
Audio surveillance: A systematic review
Despite surveillance systems becoming increasingly ubiquitous in our living environment,
automated surveillance, currently based on video sensory modality and machine …
automated surveillance, currently based on video sensory modality and machine …
Audio surveillance of roads: A system for detecting anomalous sounds
In the last decades, several systems based on video analysis have been proposed for
automatically detecting accidents on roads to ensure a quick intervention of emergency …
automatically detecting accidents on roads to ensure a quick intervention of emergency …
Spectral-spatial latent reconstruction for open-set hyperspectral image classification
Deep learning-based methods have produced significant gains for hyperspectral image
(HSI) classification in recent years, leading to high impact academic achievements and …
(HSI) classification in recent years, leading to high impact academic achievements and …