Research graph
References from DAQ-YOLO:a high precision counting model for maize seedlings in dense scenes. Local targets link to admitted publications; unresolved targets remain external evidence.
The YOLO framework: a comprehensive review of evolution, applications, and benchmarks in object detection
10.3390/computers13120336 · 2024 · External reference
Soft-NMS—improving object detection with one line of code
2017 · External reference
Benchmarking YOLO-based deep learning models for real-time object detection in hybrid ADAS and intelligent transportation systems
10.1016/j.rineng.2025.108942 · 2026 · External reference
YOLOv8-CML: a lightweight target detection method for color-changing melon ripening in intelligent agriculture
10.1038/s41598-024-65293-w · 2024 · External reference
Learning with noisy data for semi-supervised 3D object detection
2023 · External reference
Boundary IoU: improving object-centric image segmentation evaluation
2021 · External reference
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation
10.7717/peerj-cs.623 · 2021 · External reference
Maize yield prediction at an early developmental stage using multispectral images and genotype data for preliminary hybrid selection
10.3390/rs13193976 · 2021 · External reference
RepVGG: making VGG-style ConvNets great again
2021 · External reference
Global maize production, consumption and trade: trends and R&D implications
10.1007/s12571-022-01288-7 · 2022 · External reference
TOOD: task-aligned one-stage object detection
2021 · External reference
Automatic monitoring of maize seedling growth using unmanned aerial vehicle-based RGB imagery
10.3390/rs15143671 · 2023 · External reference
Global second-order pooling convolutional networks
2019 · External reference
Deep residual learning for image recognition
2016 · External reference
Coordinate attention for efficient mobile network design
2021 · External reference
Squeeze-and-excitation networks
2018 · External reference
YOLO-light-pruned: a lightweight model for monitoring maize seedling count and leaf age using near-ground and UAV RGB images
10.1016/j.aiia.2025.10.002 · 2026 · External reference
CO-YOLO: a lightweight and efficient model for Camellia oleifera fruit object detection and posture determination
10.1016/j.compag.2025.110394 · 2025 · External reference
Unresolved reference
External reference
Object detection YOLO algorithms and their industrial applications: overview and comparative analysis
10.3390/electronics14061104 · 2025 · External reference
Object detection in agriculture: a comprehensive review of methods, applications, challenges, and future directions
10.3390/agriculture15131351 · 2025 · External reference
Generalized focal loss: learning qualified and distributed bounding boxes for dense object detection
2020 · External reference
Generalized focal loss V2: learning reliable localization quality estimation for dense object detection
2021 · External reference
Neighborhood attention-based detection for maize traits in precision agriculture
10.3390/agronomy15040931 · 2025 · External reference
YOLO-FDLU: a lightweight improved YOLO11s-based algorithm for accurate maize pest and disease detection
10.3390/agriengineering7100323 · 2025 · External reference
Focal loss for dense object detection
10.1109/tpami.2018.2858826 · 2020 · External reference
SSD: single shot MultiBox detector
10.1007/978-3-319-46448-0_2 · 2016 · External reference
DMSF-YOLO: a dynamic multi-scale fusion method for maize tassel detection in UAV low-altitude remote sensing images
10.3390/agriculture15121259 · 2025 · External reference
Adaptive NMS: refining pedestrian detection in a crowd
2019 · External reference
Object detection method based on CIoU improved bounding box loss function
10.37188/cjlcd.2022-0282 · 2023 · External reference
MA-YOLO: a pest target detection algorithm with multi-scale fusion and attention mechanism
10.3390/agronomy15071549 · 2025 · External reference
An illusion predicted by V1 population activity implicates cortical topography in shape perception
10.1038/nn.3517 · 2013 · External reference
Enhancing object detection in dense images: adjustable non-maximum suppression for single-class detection
10.1109/access.2024.3459629 · 2024 · External reference
Bibliometric trends and insights into the potential of maize (Zea mays) under the framework of conservation agriculture
10.3390/su16198670 · 2024 · External reference
You only look once: unified, real-time object detection
2016 · External reference
Faster R-CNN: towards real-time object detection with region proposal networks
10.1109/tpami.2016.2577031 · 2017 · External reference
Crops that feed the world 6. Past successes and future challenges to the role played by maize in global food security
10.1007/s12571-011-0140-5 · 2011 · External reference
Weighted boxes fusion: ensembling boxes from different object detection models
10.1016/j.imavis.2021.104117 · 2021 · External reference
Dynamic group convolution for accelerating convolutional neural networks
10.1007/978-3-030-58539-6_9 · 2020 · External reference
Learning to rank proposals for object detection
2019 · External reference
A comprehensive review of YOLO architectures in computer vision: from YOLOv1 to YOLOv8 and YOLO-NAS
10.3390/make5040083 · 2023 · External reference
YOLOv10: real-time end-to-end object detection
10.52202/079017-3429 · 2024 · External reference
YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
2023 · External reference
YOLOv9: learning what you want to learn using programmable gradient information
2024 · External reference
Efficient detection and counting method for maize seedling plots
10.1016/j.atech.2025.100914 · 2025 · External reference
AdaGC: a novel adaptive optimization algorithm with gradient bias correction
10.1016/j.eswa.2024.124956 · 2024 · External reference
ECA-Net: efficient channel attention for deep convolutional neural networks
2020 · External reference
Fully learnable group convolution for acceleration of deep neural networks
2019 · External reference
Repulsion loss: detecting pedestrians in a crowd
2018 · External reference
CBAM: convolutional block attention module
10.1007/978-3-030-01234-2_1 · 2018 · External reference
SGW-YOLOv8n: an improved YOLOv8n-based model for apple detection and segmentation in complex orchard environments
10.3390/agriculture14111958 · 2024 · External reference
Boosting detection in crowd analysis via underutilized output features
2023 · External reference
Plant recognition of maize seedling stage in UAV remote sensing images based on H-RT-DETR
10.1186/s13007-025-01382-9 · 2025 · External reference
Corn leaf spot disease recognition based on improved YOLOv8
10.3390/agriculture14050666 · 2024 · External reference
A new logarithmic normalization method in games theory
10.15388/informatica.2008.215 · 2008 · External reference
Focal and efficient IoU loss for accurate bounding box regression
10.1016/j.neucom.2022.07.042 · 2022 · External reference
VarifocalNet: an IoU-aware dense object detector
2021 · External reference
Distance-IoU loss: faster and better learning for bounding box regression
10.1609/aaai.v34i07.6999 · 2020 · External reference
