A Convolutional Neural Networks Approach to Audio Classification for Rainfall Estimation

被引：0
|
作者：
Avanzato, Roberta [1 ]
Beritelli, Francesco [1 ]
Di Franco, Francesco [1 ]
Puglisi, Valerio Francesco [1 ]
机构：
[1] Univ Catania, Dept Elect Elect & Comp Engn, Catania, Italy
来源：
PROCEEDINGS OF THE 2019 10TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS - TECHNOLOGY AND APPLICATIONS (IDAACS), VOL. 1 | 2019年
关键词：
Audio classification; Enviroment sound classification; Feature extraction techniques; Convolutional Neural Networks; Rainfall Estimation;
D O I：
10.1109/idaacs.2019.8924399
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The recent climatic changes imply an increasing manifestation of calamitous phenomena related to important hydrogeological disruptions in many parts of the earth. For this reason, an accurate estimate of rainfall levels becomes essential to be able to warn of the imminent occurrence of a calamitous event and reduce the risk to human beings. This paper proposes an approach based on Convolutional Neural Networks (CNN) to the classification of the audio signal coming from a new rainfall system.
引用
收藏
页码：285 / 289
页数：5
相关论文
共 50 条
  • [1] An Ensemble of Convolutional Neural Networks for Audio Classification
    Nanni, Loris
    Maguolo, Gianluca
    Brahnam, Sheryl
    Paci, Michelangelo
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (13):
  • [2] Audio classification using braided convolutional neural networks
    Sinha, Harsh
    Awasthi, Vinayak
    Ajmera, Pawan K.
    [J]. IET SIGNAL PROCESSING, 2020, 14 (07) : 448 - 454
  • [3] Ensemble of convolutional neural networks to improve animal audio classification
    Loris Nanni
    Yandre M. G. Costa
    Rafael L. Aguiar
    Rafael B. Mangolin
    Sheryl Brahnam
    Carlos N. Silla
    [J]. EURASIP Journal on Audio, Speech, and Music Processing, 2020
  • [4] Ensemble of convolutional neural networks to improve animal audio classification
    Nanni, Loris
    Costa, Yandre M. G.
    Aguiar, Rafael L.
    Mangolin, Rafael B.
    Brahnam, Sheryl
    Silla Jr, Carlos N.
    [J]. EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING, 2020, 2020 (01)
  • [5] What Affects the Performance of Convolutional Neural Networks for Audio Event Classification
    Wang, Helin
    Chong, Dading
    Huang, Dongyan
    Zou, Yuexian
    [J]. 2019 8TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION WORKSHOPS AND DEMOS (ACIIW), 2019, : 140 - 146
  • [6] Audio Classification of Low Feature Spectrograms Utilizing Convolutional Neural Networks
    Elias, Noel
    [J]. 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, 2022, : 693 - 698
  • [7] Benchmarking Audio Signal Representation Techniques for Classification with Convolutional Neural Networks
    Sharan, Roneel, V
    Xiong, Hao
    Berkovsky, Shlomo
    [J]. SENSORS, 2021, 21 (10)
  • [8] Convolutional Neural Networks Approach for Music Genre Classification
    Cheng, Yu-Huei
    Chang, Pang-Ching
    Kuo, Che-Nan
    [J]. 2020 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C 2020), 2021, : 399 - 403
  • [9] An Approach for Thoracic Syndrome Classification with Convolutional Neural Networks
    Juneja, Sapna
    Juneja, Abhinav
    Dhiman, Gaurav
    Behl, Sanchit
    Kautish, Sandeep
    [J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2021, 2021
  • [10] Detecting Aedes aegypti mosquitoes through audio classification with convolutional neural networks
    Fernandes, Marcelo Schreiber
    Cordeiro, Weverton
    Recamonde-Mendoza, Mariana
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2021, 129
12345