Environmental audio scene and sound event recognition for autonomous surveillance: A survey and comparative studies
S Chandrakala, SL Jayalakshmi - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Monitoring of human and social activities is becoming increasingly pervasive in our living
environment for public security and safety applications. The recognition of suspicious events …
environment for public security and safety applications. The recognition of suspicious events …
Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
Spatiotemporal data mining: a survey on challenges and open problems
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …
between space and time. Several available surveys capture STDM advances and report a …
Review of random forest classification techniques to resolve data imbalance
In this current age, numerous ranges of real word applications with imbalanced dataset is
one of the foremost focal point of researcher's inattention. There is the enormous increment …
one of the foremost focal point of researcher's inattention. There is the enormous increment …
[PDF][PDF] Rare Sound Event Detection Using 1D Convolutional Recurrent Neural Networks.
Rare sound event detection is a newly proposed task in IEEE DCASE 2017 to identify the
presence of monophonic sound event that is classified as an emergency and to detect the …
presence of monophonic sound event that is classified as an emergency and to detect the …
Tmac: Temporal multi-modal graph learning for acoustic event classification
Audiovisual data is everywhere in this digital age, which raises higher requirements for the
deep learning models developed on them. To well handle the information of the multi-modal …
deep learning models developed on them. To well handle the information of the multi-modal …
You only hear once: a YOLO-like algorithm for audio segmentation and sound event detection
Audio segmentation and sound event detection are crucial topics in machine listening that
aim to detect acoustic classes and their respective boundaries. It is useful for audio-content …
aim to detect acoustic classes and their respective boundaries. It is useful for audio-content …
Sound event detection via dilated convolutional recurrent neural networks
Convolutional recurrent neural networks (CRNNs) have achieved state-of-the-art
performance for sound event detection (SED). In this paper, we propose to use a dilated …
performance for sound event detection (SED). In this paper, we propose to use a dilated …
Prediction of digital terrestrial television coverage using machine learning regression
Appropriate coverage prediction is a fundamental task for an operator during the
dimensioning process and planning of a digital terrestrial television (DTT) system because it …
dimensioning process and planning of a digital terrestrial television (DTT) system because it …
Audio scene classification with deep recurrent neural networks
We introduce in this work an efficient approach for audio scene classification using deep
recurrent neural networks. An audio scene is firstly transformed into a sequence of high …
recurrent neural networks. An audio scene is firstly transformed into a sequence of high …