# Deep spatio-textural feature driven multi-constraints pool-based active learning model for resource-efficient big earth observations

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-spatio-textural-feature-driven-multi-constraints-pool-based-active-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | N Supritha,Narasimha Murthy M S |
| Citations | 1 |
| DOI | 10.1080/01431161.2025.2457128 |
| Fields | Computer Science,Earth and Planetary Sciences,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4407298074 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Narasimha Murthy M S](https://scholariq.org/researchers/narasimha-murthy-m-s/)

## Paper primary topic

- [Remote-Sensing Image Classification](https://scholariq.org/topics/remote-sensing-image-classification/)

## Paper topics

- [Remote-Sensing Image Classification](https://scholariq.org/topics/remote-sensing-image-classification/)
- [Geochemistry and Geologic Mapping](https://scholariq.org/topics/geochemistry-and-geologic-mapping/)
- [Remote Sensing and Land Use](https://scholariq.org/topics/remote-sensing-and-land-use/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.