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Drone-Based Visible-Thermal Fusion Image Dataset for Wildlife Species Detection at Baluran National Park, Indonesia

Dede Aulia Rahman, Toto Haryanto, Christiawan Eko Saputro

This dataset is associated with the study: "First use of visible-thermal fusion network approach for robust species monitoring in the tropics".A total of 797 fused visible-thermal drone images were collected at Baluran National Park, East Java, Indonesia. The park is a tropical savanna ecosystem and a key conservation area for several protected and near-threatened species in Java.All images provided in this dataset are fusion outputs — composite images combining visible (RGB) and thermal infrared information — and were used directly as input for deep learning-based species detection models Dataset summary:Total images: 797 fused visible-thermal imagesImage type: Fusion output (not raw RGB or thermal)Annotations: Not included (image-only release)Capture platform: UAV dual-sensor systemStudy site: Baluran National Park, Situbondo, East Java, IndonesiaHabitat: Tropical savanna

Also available via: European Organization for Nuclear Research

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openalexZenodo (CERN European Organization for Nuclear Research)

Dataset for Wildlife Species Detection at Baluran National Park, Indonesia

Dede Aulia Rahman, Toto Haryanto, Christiawan Eko Saputro

This dataset is associated with the study: "First use of visible-thermal fusion network approach for robust species monitoring in the tropics".A total of 797 fused visible-thermal drone images were collected at Baluran National Park, East Java, Indonesia. The park is a tropical s…

Also available via: European Organization for Nuclear Research

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23

Microgreen Master Dataset (Public Version): RGB Image Dataset for Classification of Healthy, Dry, and Mold-Affected Microgreens

Ganna Zavolodko, Volodymyr Andriushchenko

The Microgreen Master Dataset (Public Version) is an open RGB image dataset developed to support research in computer vision, artificial intelligence, and smart agriculture. The dataset is intended for training and evaluating machine learning models for automatic classification o…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-08-09

Multi-Model Comparative Study for Bark-Texture Based Tree Species Classification Using Custom Indian Tree Species Dataset

Shaila Doddamani, Apeksha Kule

Accurate wood species identification is crucial for biodiversity preservation and forest management. Because traditional identification methods are time-consuming and heavily rely on expert knowledge, automated image-based solutions have become more and more important. This resea…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

Assistive Belt Outdoor Navigation Dataset for Visually Impaired: 15-Class Object Detection Dataset (YOLO Format)

Hanane Lachoub

This dataset was developed to support an assistive belt system designed to help visually impaired individuals navigate outdoor environments safely. It contains annotated images covering 15 object classes relevant to outdoor navigation: person, car, bus, truck, bicycle, motorcycle…

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openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

Sentinel-1/2 benchmark dataset for BS for segmentation Intertidal Biogenic Structures in the Lower Saxony Wadden Sea National Park

Armin Moghimi

This dataset was developed for the manuscript entitled “A Sentinel-1/2 Benchmark Dataset and Deep Learning Models for Segmenting Intertidal Biogenic Structures in the Lower Saxony Wadden Sea National Park,” which is currently under review. At this stage, the dataset is provided e…

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openalexZenodo (CERN European Organization for Nuclear Research)

Learning Perceptual Hash Similarity for Image Copy Detection

Maria Pegia, Dimitrios Stefanopoulos, Björn Þór Jónsson, Anastasia Moumtzidou, Ilias Gialampoukidis, Stefanos Vrochidis, et al.

Image copy detection is commonly addressed using either local descriptors or deep learning models, which can be computationally expensive and rely on high-dimensional features. In contrast, this work explores copy detection using compact perceptual hash representations and learne…

Also available via: European Organization for Nuclear Research

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