ArticlePlants (Basel, Switzerland)2024
Chili Pepper Object Detection Method Based on Improved YOLOv8n.
Article in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- SLP-Net: A Dual-Level Contrastive Learning Framework with Stripe Attention for Elongated Pepper Detection in Complex Field Environments.Plants (Basel, Switzerland) · 2026Article
- Explainable YOLO architectures for egg size measurement and classification.Scientific reports · 2026Article
- HAV-Pose: synergizing hybrid attention networks and spherical visibility fields for obstacle-aware fruit harvesting.Frontiers in plant science · 2026Article
- RGC-YOLO: a lightweight YOLOv8n-based detector for edge-deployable weed detection in Xinjiang cotton fields.Frontiers in plant science · 2026Article
- UAV-Based Automatic Detection of Missing Rice Seedlings Using the PCERT-DETR Model.Plants (Basel, Switzerland) · 2025Article
- Sustainable deep vision systems for date fruit quality assessment using attention-enhanced deep learning models.Frontiers in plant science · 2025Article
- Kidney bean detection in complex agricultural scenarios based on the kidneyB-YOLO model.Frontiers in plant science · 2025Article
- YOLOv8-CBAM: a study of sheep head identification in Ujumqin sheep.Frontiers in veterinary science · 2025Article
- Field-deployable lightweight YOLOv8n for real-time detection and counting of Maize seedlings using UAV RGB imagery.Frontiers in plant science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
In response to the low accuracy and slow detection speed of chili recognition in natural environments, this study proposes a chili pepper object detection method based on the improved YOLOv8n. Evaluations were conducted among YOLOv5n, YOLOv6n, YOLOv7-tiny, YOLOv8n, YOLOv9, and YOLOv10 to select the optimal model. YOLOv8n was chosen as the baseline and improved as follows: (1) Replacing the YOLOv8 backbone with the improved HGNetV2 model to reduce floating-point operations and computational load during convolution. (2) Integrating the SEAM (spatially enhanced attention module) into the YOLOv8 detection head to enhance feature extraction capability under chili fruit occlusion. (3) Optimizing feature fusion using the dilated reparam block module in certain C2f (CSP bottleneck with two convolutions). (4) Substituting the traditional upsample operator with the CARAFE(content-aware reassembly of features) upsampling operator to further enhance network feature fusion capability and improve detection performance. On a custom-built chili dataset, the F
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.