Synthetic Apple Collection

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Authors: Jhonny Hueller, Massimo Vecchio, Fabio Antonelli
Cited by: 0

Abstract

The Synthetic Apple Collection (SyntAC) is a suite of three synthetic datasets (Synthetic A, B, and C) designed to advance computer vision applications in precision agriculture. SyntAC provides a scalable and cost-effective alternative to manually annotated real-world imagery. The collection was generated using a fully procedural pipeline in Blender and Unreal Engine 5, with each tier (A → C) progressively refined to align scene composition and annotation geometry with high-performing real-world benchmarks.

Fields of Study & Subjects

Smart Agriculture and AI Advanced Neural Network Applications Industrial Vision Systems and Defect Detection

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
5 February 2026
Document type
Dataset