Research graph
References from A Lightweight Attention-Based Model for Real-Time Weed Detection and Edge Deployment in Angelica dahurica Fields. Local targets link to admitted publications; unresolved targets remain external evidence.
10.3389/fphar.2022.896637
10.3389/fphar.2022.896637 · External reference
A Review of the Historical Records, Chemistry, Pharmacology, Pharmacokinetics and Edibility of Angelica dahurica
10.1016/j.arabjc.2023.104877 · 2023 · External reference
Sustainable Utilization of Traditional Chinese Medicine Resources: Systematic Evaluation on Different Production Modes
2015 · External reference
10.3390/agronomy16090901
10.3390/agronomy16090901 · External reference
Review of Current Robotic Approaches for Precision Weed Management
10.1007/s43154-022-00086-5 · 2022 · External reference
Advances in Ground Robotic Technologies for Site-Specific Weed Management in Precision Agriculture: A Review
10.1016/j.compag.2024.109363 · 2024 · External reference
10.3390/s24206743
10.3390/s24206743 · External reference
10.3390/agronomy14020363
10.3390/agronomy14020363 · External reference
Deep Learning Techniques for In-Crop Weed Recognition in Large-Scale Grain Production Systems: A Review
10.1007/s11119-023-10073-1 · 2024 · External reference
A Survey of Deep Learning Techniques for Weed Detection from Images
10.1016/j.compag.2021.106067 · 2021 · External reference
Unresolved reference
External reference
10.1007/978-3-319-46448-0_2
10.1007/978-3-319-46448-0_2 · External reference
10.1109/iccv.2017.324
10.1109/iccv.2017.324 · External reference
10.1109/cvpr42600.2020.01079
10.1109/cvpr42600.2020.01079 · External reference
10.1109/cvpr.2016.91
10.1109/cvpr.2016.91 · External reference
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
10.1038/s41598-018-38343-3 · 2019 · External reference
10.3389/fpls.2022.850666
10.3389/fpls.2022.850666 · External reference
10.3390/agronomy12071580
10.3390/agronomy12071580 · External reference
10.3390/su142215088
10.3390/su142215088 · External reference
10.1109/cvpr52729.2023.00721
10.1109/cvpr52729.2023.00721 · External reference
Unresolved reference
External reference
Recognizing Weed in Rice Field Using ViT-Improved YOLOv7
2024 · External reference
10.3390/agronomy14102363
10.3390/agronomy14102363 · External reference
10.3390/s24134379
10.3390/s24134379 · External reference
10.3390/agriculture15010022
10.3390/agriculture15010022 · External reference
10.3390/plants13131843
10.3390/plants13131843 · External reference
10.3390/agronomy14123062
10.3390/agronomy14123062 · External reference
10.3390/agriculture15181971
10.3390/agriculture15181971 · External reference
10.3390/agriculture14122134
10.3390/agriculture14122134 · External reference
Towards Real-Time Weed Detection and Segmentation with Lightweight CNN Models on Edge Devices
10.1016/j.compag.2025.110600 · 2025 · External reference
Agricultural Weed Identification in Images and Videos by Integrating Optimized Deep Learning Architecture on an Edge Computing Technology
10.1016/j.compag.2023.108442 · 2024 · External reference
YOLOv7-CBAM and DeepSORT with Pixel Grid Analysis for Real-Time Weed Localization and Intra-Row Density Estimation in Apple Orchards
10.1016/j.compag.2025.111071 · 2026 · External reference
A Survey on Image Data Augmentation for Deep Learning
10.1186/s40537-019-0197-0 · 2019 · External reference
Unresolved reference
External reference
SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
2021 · External reference
Focal and Efficient IOU Loss for Accurate Bounding Box Regression
10.1016/j.neucom.2022.07.042 · 2022 · External reference
Unresolved reference
External reference
10.1007/978-3-319-10602-1_48
10.1007/978-3-319-10602-1_48 · External reference
10.1109/iccv.2017.74
10.1109/iccv.2017.74 · External reference
Unresolved reference
External reference
10.1007/978-3-319-10602-1_48
10.1007/978-3-319-10602-1_48 · ExternalCitation · doi-reference
10.1007/978-3-319-46448-0_2
10.1007/978-3-319-46448-0_2 · ExternalCitation · doi-reference
Deep Learning Techniques for In-Crop Weed Recognition in Large-Scale Grain Production Systems: A Review
10.1007/s11119-023-10073-1 · ExternalCitation · doi-reference
Review of Current Robotic Approaches for Precision Weed Management
10.1007/s43154-022-00086-5 · ExternalCitation · doi-reference
A Review of the Historical Records, Chemistry, Pharmacology, Pharmacokinetics and Edibility of Angelica dahurica
10.1016/j.arabjc.2023.104877 · ExternalCitation · doi-reference
A Survey of Deep Learning Techniques for Weed Detection from Images
10.1016/j.compag.2021.106067 · ExternalCitation · doi-reference
Agricultural Weed Identification in Images and Videos by Integrating Optimized Deep Learning Architecture on an Edge Computing Technology
10.1016/j.compag.2023.108442 · ExternalCitation · doi-reference
Advances in Ground Robotic Technologies for Site-Specific Weed Management in Precision Agriculture: A Review
10.1016/j.compag.2024.109363 · ExternalCitation · doi-reference
Towards Real-Time Weed Detection and Segmentation with Lightweight CNN Models on Edge Devices
10.1016/j.compag.2025.110600 · ExternalCitation · doi-reference
YOLOv7-CBAM and DeepSORT with Pixel Grid Analysis for Real-Time Weed Localization and Intra-Row Density Estimation in Apple Orchards
10.1016/j.compag.2025.111071 · ExternalCitation · doi-reference
Focal and Efficient IOU Loss for Accurate Bounding Box Regression
10.1016/j.neucom.2022.07.042 · ExternalCitation · doi-reference
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
10.1038/s41598-018-38343-3 · ExternalCitation · doi-reference
10.1109/cvpr.2016.91
10.1109/cvpr.2016.91 · ExternalCitation · doi-reference
10.1109/cvpr42600.2020.01079
10.1109/cvpr42600.2020.01079 · ExternalCitation · doi-reference
10.1109/cvpr52729.2023.00721
10.1109/cvpr52729.2023.00721 · ExternalCitation · doi-reference
10.1109/iccv.2017.324
10.1109/iccv.2017.324 · ExternalCitation · doi-reference
10.1109/iccv.2017.74
10.1109/iccv.2017.74 · ExternalCitation · doi-reference
A Survey on Image Data Augmentation for Deep Learning
10.1186/s40537-019-0197-0 · ExternalCitation · doi-reference
10.3389/fphar.2022.896637
10.3389/fphar.2022.896637 · ExternalCitation · doi-reference
10.3389/fpls.2022.850666
10.3389/fpls.2022.850666 · ExternalCitation · doi-reference
10.3390/agriculture14122134
10.3390/agriculture14122134 · ExternalCitation · doi-reference
10.3390/agriculture15010022
10.3390/agriculture15010022 · ExternalCitation · doi-reference
10.3390/agriculture15181971
10.3390/agriculture15181971 · ExternalCitation · doi-reference
10.3390/agronomy12071580
10.3390/agronomy12071580 · ExternalCitation · doi-reference
10.3390/agronomy14020363
10.3390/agronomy14020363 · ExternalCitation · doi-reference
10.3390/agronomy14102363
10.3390/agronomy14102363 · ExternalCitation · doi-reference
10.3390/agronomy14123062
10.3390/agronomy14123062 · ExternalCitation · doi-reference
10.3390/agronomy16090901
10.3390/agronomy16090901 · ExternalCitation · doi-reference
10.3390/plants13131843
10.3390/plants13131843 · ExternalCitation · doi-reference
10.3390/s24134379
10.3390/s24134379 · ExternalCitation · doi-reference
10.3390/s24206743
10.3390/s24206743 · ExternalCitation · doi-reference
10.3390/su142215088
10.3390/su142215088 · ExternalCitation · doi-reference
