arXiv:2208.01555
Low-complexity CNNs for Acoustic Scene Classification
원문 초록
This technical report describes the SurreyAudioTeam22s submission for DCASE 2022 ASC Task 1, Low-Complexity Acoustic Scene Classification (ASC). The task has two rules, (a) the ASC framework should have maximum 128K parameters, and (b) there should be a maximum of 30 millions multiply-accumulate operations (MACs) per inference. In this report, we present low-complexity systems for ASC that follow the rules intended for the task.
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Low-Complexity Acoustic Scene Classification with Device Information in the DCASE 2025 Challenge
Self-Attention-Based Deep Feature Fusion for Remote Sensing Scene Classification
Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments
Generalized Scene Classification from Small-Scale Datasets with Multi-Task Learning
Spatial Information Considered Network for Scene Classification
Efficient Calisthenics Skills Classification through Foreground Instance Selection and Depth Estimation
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