A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...
Please note that the dataset used to train this model is a custom-created, ultra-high-quality dataset derived from MS-COCO. Therefore, a simple comparison with the Val mAP values of other object ...
With the rapid development of marine resource exploitation and the increasing demand for underwater robot inspection, achieving reliable target perception in turbid, low-illumination, and spectrally ...
Abstract: Weakly supervised object detection (WSOD) in remote sensing images (RSIs) only requires image-level labels, greatly reducing the cost of manual annotations. Recently, the pseudo-fully ...
Abstract: Aphids are among the most destructive pests that threaten global crop yields, harming crops through feeding and virus transmission. Accurate detection of aphids in fields is a crucial step ...
Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...
To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...
As an important economic crop, apples are significantly affected by disease infestations, which can lead to substantial reductions in apple yield and economic losses. To rapidly and accurately detect ...
This project focuses on building a robust object detection model for self-checkout systems, specifically targeting apple detection. While standard models like SSD and Faster R-CNN struggled with ...
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