mlsanityData to 7 Oct 2026

Descriptor: Parasitoid Wasps and Associated Hymenoptera Dataset (DAPWH)

arXiv 2602.20028 ↗First posted 20 Feb 2026cs.CV cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Accurate taxonomic identification is the cornerstone of biodiversity monitoring and agricultural management, particularly for the hyper-diverse superfamily Ichneumonoidea. Comprising the families Ichneumonidae and Braconidae, these parasitoid wasps are ecologically critical for regulating insect populations, yet they remain one of the most taxonomically challenging groups due to their cryptic morphology and vast number of undescribed species. To address the scarcity of robust digital resources for these key groups, we present a curated image dataset designed to advance automated identification systems. The dataset contains 3,556 high-resolution images, primarily focused on Neotropical Ichneumonidae and Braconidae, while also including supplementary families such as Andrenidae, Apidae, Bethylidae, Chrysididae, Colletidae, Halictidae, Megachilidae, Pompilidae, and Vespidae to improve model robustness. Crucially, a subset of 1,739 images is annotated in COCO format, featuring multi-class bounding boxes for the full insect body, wing venation, and scale bars. This resource provides a foundation for developing computer vision models capable of identifying these families.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 37 references that are in the map. First posted on arXiv 20 Feb 2026.

Builds on

9 of 37 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  5. 2023Segment Anythingcited by 8,158
  6. 2022A ConvNet for the 2020scited by 3,545
  7. 2021EfficientNetV2: Smaller Models and Faster Trainingcited by 1,127
  8. 2025YOLOv12: Attention-Centric Real-Time Object Detectorscited by 300
  9. 2018Model Evaluation, Model Selection, and Algorithm Selection in Machine Learningcited by 157

Built on by

Not cited yet.