ArticleFrontiers in plant science2023
An improved YOLOv5s model using feature concatenation with attention mechanism for real-time fruit detection and counting.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 21 citations in OpenAlex.
- AxiWorm: a new tool using YOLOv5 to test antiparasitic drugs against Trichinella spiralis.Parasites & vectors · 2025Article
- Article
- MDE-DETR: multi-domain enhanced feature fusion algorithm for bayberry detection and counting in complex orchards.Frontiers in plant science · 2025Article
- An anchor-based YOLO fruit detector developed on YOLOv5.PloS one · 2025Article
- Design and experiment of miss-seeding detection and preparatory seed scraper-belt compensation mechanism based on improved YOLOv5s for potato seed-metering devices.Frontiers in plant science · 2025Article
- Research on target localization and adaptive scrubbing of intelligent bathing assistance system.Frontiers in bioengineering and biotechnology · 2025Article
- YOLOv8s-Longan: a lightweight detection method for the longan fruit-picking UAV.Frontiers in plant science · 2024Article
- A simplified network topology for fruit detection, counting and mobile-phone deployment.PloS one · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An improved YOLOv5s model was proposed and validated on a new fruit dataset to solve the real-time detection task in a complex environment. With the incorporation of feature concatenation and an attention mechanism into the original YOLOv5s network, the improved YOLOv5s recorded 122 layers, 4.4 × 10
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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.