arXiv AI July 17, 2026 By Joao Manoel Herrera Pinheiro, Gabriela Do Nascimento Herrera, Alvaro Doria Dos Santos, Luciana Bueno Dos Reis Fernandes, Ricardo V. Godoy, Eduardo A. B. Almeida, Helena Carolina Onody, Marcelo Andrade Da Costa Vieira, Angelica Maria Penteado-Dias, Marcelo Becker

Automated identification of Ichneumonoidea wasps via YOLO-based deep learning: Integrating HiresCam for Explainable AI

Read the original on arXiv AI →

arXiv:2603. 16351v2 Announce Type: replace-cross Abstract: Accurate taxonomic identification of parasitoid wasps within the superfamily Ichneumonoidea is essential for biodiversity assessment, ecological monitoring, and biological control programs.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning

Jun 19

A High-Resolution Landscape Dataset for Concept-Based XAI With Application to Species Distribution Models

arXiv:2604. 13240v2 Announce Type: replace-cross Abstract: Mapping the spatial distribution of species is essential for conservation policy and invasive species management.

By Augustin de la Brosse, Damien Garreau, Thomas Houet, Thomas Corpetti

llms computer-vision robotics

arXiv AI

Jun 29

Explainable AI for Biodiversity Monitoring and Ecological Image Analysis

arXiv:2606. 27667v1 Announce Type: cross Abstract: Artificial intelligence is transforming biodiversity monitoring by enabling automated analysis of ecological imagery collected from camera traps, drones, satellites, underwater platforms, and other sensing systems.

By Brinnae Bent, Holly R. Houliston, Jiayi Zhou, G\"unel Aghakishiyeva, David W. Johnston

computer-vision

arXiv Machine Learning

Jun 25

Taxonomy-aware deep learning for hierarchical marine species classification in underwater imagery

arXiv:2606. 25989v1 Announce Type: cross Abstract: Automated classification of marine species from underwater imagery is essential for scalable ocean biodiversity monitoring and conservation policy.

By Dan Zimmerman, Dimitris A. Pados, George Sklivanitis

arXiv AI

Jul 31

Multimodal fusion of visual and morphometric features for avian bone classification

arXiv:2607. 26743v1 Announce Type: cross Abstract: Artificial intelligence has shown considerable potential for archaeological applications, yet its use in zooarchaeology remains limited, particularly for the identification of avian skeletal remains.

By Nevio Dubbini, Lisa Yeomans, Marco Pavia, Ramazan Parmaksiz, Ayse Atas Hooglugt, Gabriele Gattiglia, Beatrice Demarchi

multimodal

arXiv Machine Learning

Jun 26

Batch-Invariant Spectral Intelligence for Robust and Explainable Insect Authentication

arXiv:2606. 26757v1 Announce Type: new Abstract: Edible insects offer an efficient source of alternative protein, requiring less land, water and emitting less greenhouse gas than conventional livestock.

By Majharulislam Babor, Giacomo Rossi, Annalisa Altavilla, Oliver Schl\"uter, Marina M. -C. H\"ohne

fine-tuning safety

arXiv AI

Aug 11

TomaMMU: A Comprehensive Multimodal Understanding Benchmark for Tomato Leaf Diseases

arXiv:2608. 08727v1 Announce Type: cross Abstract: To address this gap, we introduce TomaMMU, a large-scale Tomato leaf disease MultiModal Understanding dataset, alongside TomaBench, a benchmark for evaluating VLMs on tomato disease understanding.

By Gia-Han Truong, Khang Nguyen Quoc, Luyl-Da Quach

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