MWIRSTD: A MWIR Small Target Detection Dataset

This paper presents a novel mid-wave infrared (MWIR) small target detection dataset (MWIRSTD) comprising 14 video sequences containing approximately 1053 images with annotated targets of three distinct classes of small objects. Captured using cooled MWIR imagers, the dataset offers a unique opportunity for researchers to develop and evaluate state-of-the-art methods for small object detection in realistic MWIR scenes. Unlike existing datasets, which primarily consist of uncooled thermal images or synthetic data with targets superimposed onto the background or vice versa, MWIRSTD provides authentic MWIR data with diverse targets and environments. Extensive experiments on various traditional methods and deep learning-based techniques for small target detection are performed on the proposed dataset, providing valuable insights into their efficacy. The dataset and code are available at https://github.com/avinres/MWIRSTD.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/icip51287.2024.10648074
Citations
3
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
1.04
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article

MWIRSTD: A MWIR Small Target Detection Dataset

Pravendra Singh, Shreya Sharma, Avinash Upadhyay, Nikhil Kumar et al.
3 citations
AI in cancer detection
1.04
article

MWIRSTD: A MWIR Small Target Detection Dataset

Pravendra Singh, Shreya Sharma, Avinash Upadhyay, Nikhil Kumar, Manoj Sharma
article en
3 citations

Abstract

This paper presents a novel mid-wave infrared (MWIR) small target detection dataset (MWIRSTD) comprising 14 video sequences containing approximately 1053 images with annotated targets of three distinct classes of small objects. Captured using cooled MWIR imagers, the dataset offers a unique opportunity for researchers to develop and evaluate state-of-the-art methods for small object detection in realistic MWIR scenes. Unlike existing datasets, which primarily consist of uncooled thermal images or synthetic data with targets superimposed onto the background or vice versa, MWIRSTD provides authentic MWIR data with diverse targets and environments. Extensive experiments on various traditional methods and deep learning-based techniques for small target detection are performed on the proposed dataset, providing valuable insights into their efficacy. The dataset and code are available at https://github.com/avinres/MWIRSTD.

Indian Institute of Technology Roorkee (IN), Bennett University (IN)
Openalex Percentile: Top 19%
AI in cancer detection
1.04
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MWIRSTD: A MWIR Small Target Detection Dataset — Pravendra Singh, Shreya Sharma, et al. · (2024) | TGRS Research Map | TGRS