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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Visual Active Learning for Labeling: A Case for Soundscape Ecology Data

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Author(s):
Hilasaca, Liz Huancapaza [1] ; Ribeiro, Milton Cezar [2] ; Minghim, Rosane [3]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Dept Comp Sci, BR-13566590 Sao Carlos, SP - Brazil
[2] Sao Paulo State Univ UNESP, Biodivers Dept, BR-13506900 Rio Claro, SP - Brazil
[3] Univ Coll Cork, Sch Comp Sci & Informat Technol, Cork T12 XF62 - Ireland
Total Affiliations: 3
Document type: Journal article
Source: INFORMATION; v. 12, n. 7 JUL 2021.
Web of Science Citations: 0
Abstract

Labeling of samples is a recurrent and time-consuming task in data analysis and machine learning and yet generally overlooked in terms of visual analytics approaches to improve the process. As the number of tailored applications of learning models increases, it is crucial that more effective approaches to labeling are developed. In this paper, we report the development of a methodology and a framework to support labeling, with an application case as background. The methodology performs visual active learning and label propagation with 2D embeddings as layouts to achieve faster and interactive labeling of samples. The framework is realized through SoundscapeX, a tool to support labeling in soundscape ecology data. We have applied the framework to a set of audio recordings collected for a Long Term Ecological Research Project in the Cantareira-Mantiqueira Corridor (LTER CCM), localized in the transition between northeastern Sao Paulo state and southern Minas Gerais state in Brazil. We employed a pre-label data set of groups of animals to test the efficacy of the approach. The results showed the best accuracy at 94.58% in the prediction of labeling for birds and insects; and 91.09% for the prediction of the sound event as frogs and insects. (AU)

FAPESP's process: 20/01779-5 - Biodiversity in the Anthropocene: agroecosystem effects on biodiversity conservation and ecosystem function maintenance
Grantee:Milton Cezar Ribeiro
Support Opportunities: Regular Research Grants
FAPESP's process: 13/50421-2 - New sampling methods and statistical tools for biodiversity research: integrating animal movement ecology with population and community ecology
Grantee:Milton Cezar Ribeiro
Support Opportunities: Regular Research Grants