Self-Supervised Transfer Learning from Natural Images for Sound Classification

Self-Supervised Transfer Learning from Natural Images for Sound Classification

We propose the implementation of transfer learning from natural images to audio-based images using self-supervised learning schemes. Through self-supervised learning, convolutional neural networks (CNNs) can learn the general representation of natural images without labels. In this study, a convolut...

Fuld beskrivelse

Bibliografiske detaljer
Main Authors:	Sungho Shin, Jongwon Kim, Yeonguk Yu, Seongju Lee, Kyoobin Lee
Format:	Article
Sprog:	English
Udgivet:	MDPI AG 2021-03-01
Serier:	Applied Sciences
Fag:	deep learning sound event detection self-supervised learning transfer learning natural image
Online adgang:	https://www.mdpi.com/2076-3417/11/7/3043

Lignende værker

BattleSound: A Game Sound Benchmark for the Sound-Specific Feedback Generation in a Battle Game
af: Sungho Shin, et al.
Udgivet: (2023-01-01)

Semi-Supervised NMF-CNN for Sound Event Detection
af: Teck Kai Chan, et al.
Udgivet: (2021-01-01)

Weakly Supervised U-Net with Limited Upsampling for Sound Event Detection
af: Sangwon Lee, et al.
Udgivet: (2023-06-01)

Transfer learning application of self-supervised learning in ARPES
af: Sandy Adhitia Ekahana, et al.
Udgivet: (2023-01-01)

From Self-supervised Learning to Transfer Learning with Musculoskeletal Radiographs
af: Hinterwimmer Florian, et al.
Udgivet: (2022-09-01)

Self-Supervised Learning for Solar Radio Spectrum Classification
af: Siqi Li, et al.
Udgivet: (2022-12-01)

Classification of the Sidewalk Condition Using Self-Supervised Transfer Learning for Wheelchair Safety Driving
af: Ha-Yeong Yoon, et al.
Udgivet: (2022-01-01)

Robust Skin Disease Classification by Distilling Deep Neural Network Ensemble for the Mobile Diagnosis of Herpes Zoster
af: Seunghyeok Back, et al.
Udgivet: (2021-01-01)

Sound-Event Detection of Water-Usage Activities Using Transfer Learning
af: Seung Ho Hyun
Udgivet: (2023-12-01)

Study on Human Activity Recognition Using Semi-Supervised Active Transfer Learning
af: Seungmin Oh, et al.
Udgivet: (2021-04-01)

w2v-SELD: A Sound Event Localization and Detection Framework for Self-Supervised Spatial Audio Pre-Training
af: Orlem Lima Dos Santos, et al.
Udgivet: (2024-01-01)

Patch-Level Consistency Regularization in Self-Supervised Transfer Learning for Fine-Grained Image Recognition
af: Yejin Lee, et al.
Udgivet: (2023-09-01)

Abnormal Heart Sound Classification and Model Interpretability: A Transfer Learning Approach with Deep Learning
af: Milan Marocchi, et al.
Udgivet: (2023-12-01)

Supervised contrastive pretrained ResNet with MixUp to enhance respiratory sound classification on imbalanced and limited dataset
af: Hu, Jinhai, et al.
Udgivet: (2024)

Self-supervised in-domain representation learning for remote sensing image scene classification
af: Ali Ghanbarzadeh, et al.
Udgivet: (2024-10-01)

Transfer learning for self-supervised, blind-spot seismic denoising
af: Claire Birnie, et al.
Udgivet: (2022-12-01)

Self-Supervised Assisted Semi-Supervised Residual Network for Hyperspectral Image Classification
af: Liangliang Song, et al.
Udgivet: (2022-06-01)

CLASSIFICATION BASED ON SEMI-SUPERVISED LEARNING: A REVIEW
af: Aska Ezadeen Mehyadin, et al.
Udgivet: (2021-05-01)

Contrastive Self-Supervised Learning for Sensor-Based Human Activity Recognition: A Review
af: Hui Chen, et al.
Udgivet: (2024-01-01)

Weakly Supervised Instance Segmentation Based on Two-Stage Transfer Learning
af: Yongqing Sun, et al.
Udgivet: (2020-01-01)

Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications
af: Zachary D. Calhoun, et al.
Udgivet: (2022-11-01)

Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification
af: Sebastian Otálora, et al.
Udgivet: (2021-05-01)

Research on Semi-Supervised Sound Event Detection Based on Mean Teacher Models Using ML-LoBCoD-NET
af: Jinjia Wang, et al.
Udgivet: (2020-01-01)

DimCL: Dimensional Contrastive Learning for Improving Self-Supervised Learning
af: Thanh Nguyen, et al.
Udgivet: (2023-01-01)

Image-Based Vehicle Classification by Synergizing Features from Supervised and Self-Supervised Learning Paradigms
af: Shihan Ma, et al.
Udgivet: (2023-02-01)

Weak Supervised Sound Event Detection Based on Puzzle CAM
af: Xichang Cai, et al.
Udgivet: (2023-01-01)

OVERVIEW OF COMPUTER VISION SUPERVISED LEARNING TECHNIQUES FOR LOW-DATA TRAINING
af: BURLACU, Alexandru
Udgivet: (2020-12-01)

Study of implicit information semi-supervised learning algorithm
af: Guo-dong LIU, et al.
Udgivet: (2015-10-01)

Study of implicit information semi-supervised learning algorithm
af: Guo-dong LIU, et al.
Udgivet: (2015-10-01)

Deep Transfer Learning for Machine Diagnosis: From Sound and Music Recognition to Bearing Fault Detection
af: Eugenio Brusa, et al.
Udgivet: (2021-12-01)

An improved self-supervised learning for EEG classification
af: Yanghan Ou, et al.
Udgivet: (2022-05-01)

InverseTime: A Self-Supervised Technique for Semi-Supervised Classification of Time Series
af: Manuel Alejandro Goyo, et al.
Udgivet: (2024-01-01)

Enhancing Retinal Blood Vessel Segmentation through Self-Supervised Pre-Training
af: José Morano, et al.
Udgivet: (2020-08-01)

Self-Supervised Video Representation and Temporally Adaptive Attention for Audio-Visual Event Localization
af: Yue Ran, et al.
Udgivet: (2022-12-01)

Audio-Based Emotion Recognition Using Self-Supervised Learning on an Engineered Feature Space
af: Peranut Nimitsurachat, et al.
Udgivet: (2024-01-01)

An Enhanced Contrastive Ensemble Learning Method for Anomaly Sound Detection
af: Jingneng Liao, et al.
Udgivet: (2025-02-01)

Classification of Ground-Based Cloud Images by Contrastive Self-Supervised Learning
af: Qi Lv, et al.
Udgivet: (2022-11-01)

Shifting to machine supervision: annotation-efficient semi and self-supervised learning for automatic medical image segmentation and classification
af: Pranav Singh, et al.
Udgivet: (2024-05-01)

A survey on heterogeneous transfer learning
af: Oscar Day, et al.
Udgivet: (2017-09-01)

An Effective Representation Learning Approach: The Integrated Self-Supervised Pre-Training Models of StyleGAN2-ADA and DINO for Colon Polyp Images
af: Jong-Yeup Kim, et al.
Udgivet: (2023-01-01)