Project AURIONAI Use-Cases Research & Innovation
vision

YOLOv11 FFB ripeness grader (IJCCS 2025)

Academic oil palm fresh fruit bunch ripeness detector on YOLOv11; 90.2% mAP@50. No plantation deployment stated. Affiliation unverified.

UPN Veteran Jawa Timur
Levelmodel
Classvision
Parametersnot in the notes
Contextnot in the notes
Released31 Oct 2025
Opennessunknown
Runs onCPU server, offline capable
Statusnot in the notes

Lineage

successorfinetune
YOLO11 to YOLO26: successor, medium confidenceYOLO11 to YOLOv11 FFB ripeness grader (IJCCS 2025): finetune, medium confidenceYOLO11YOLO11Ultralytics, Oct 2024YOLOv11 FFB ripeness grader (IJCCS 2025)YOLOv11 FFB ripeness grade…UPN Veteran Jawa Timur, Oct 2025YOLO26YOLO26Ultralytics, Jan 2026
UltralyticsYOLO11 is the parent (finetune)medium confidencenotes
Where this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 3 models. Confidence and evidence are the notes' own.

Industry Use Cases

R&D Topics

Identity

Developer
UPN Veteran Jawa Timur
Family
not in the notes
Released
31 Oct 2025 sourcesnotes
Weights published
–
Record checked
10 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
CNN
Total parameters
– sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
image
Output
not in the notes
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
unknown
Licence
not in the notes sources
Access routes
research only
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
CPU server, offline capable
Footprint
ONNX Runtime on CPU; 255 to 300 ms latency
Runtimes
not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Benchmark Results

The notes record no benchmark result for this model.

Sources

  1. Optimization of Palm Fruit Ripeness Detection With Yolov11 on CPU | Anniswa | IJCCS (Indonesian Journal of Computing and Cybernetics Systems journal.ugm.ac.id https://journal.ugm.ac.id/ijccs/article/view/111253

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "YOLOv11 FFB Ripeness Grader (IJCCS 2025)", https://aurion.semai.id/models/upn-veteran-jawa-timur-yolov11-ffb-grader/, records of October 2026.