A review of deep learning in multiscale agricultural sensing
Population growth, climate change, and the worldwide COVID-19 pandemic are imposing
increasing pressure on global agricultural production. The challenge of increasing crop yield …
increasing pressure on global agricultural production. The challenge of increasing crop yield …
Classification and detection of insects from field images using deep learning for smart pest management: A systematic review
W Li, T Zheng, Z Yang, M Li, C Sun, X Yang - Ecological Informatics, 2021 - Elsevier
Insect pest is one of the main causes affecting agricultural crop yield and quality all over the
world. Rapid and reliable insect pest monitoring plays a crucial role in population prediction …
world. Rapid and reliable insect pest monitoring plays a crucial role in population prediction …
RDD-YOLO: A modified YOLO for detection of steel surface defects
C Zhao, X Shu, X Yan, X Zuo, F Zhu - Measurement, 2023 - Elsevier
Steel surfaces may exist some defects owing to imperfect manufacturing crafts and external
factors, which seriously influence the lifespan and availability of steel. Thus, surface defect …
factors, which seriously influence the lifespan and availability of steel. Thus, surface defect …
Deep learning based detector YOLOv5 for identifying insect pests
Insect pests are a major element influencing agricultural production. According to the Food
and Agriculture Organization (FAO), an estimated 20–40% of pest damage occurs each …
and Agriculture Organization (FAO), an estimated 20–40% of pest damage occurs each …
MD-YOLO: Multi-scale Dense YOLO for small target pest detection
Y Tian, S Wang, E Li, G Yang, Z Liang, M Tan - Computers and Electronics …, 2023 - Elsevier
The detection of pests plays a crucial role in intelligent early warning systems of injurious
insects and diseases in precision agriculture. However, pests strong concealment and …
insects and diseases in precision agriculture. However, pests strong concealment and …
Plant disease detection and classification method based on the optimized lightweight YOLOv5 model
H Wang, S Shang, D Wang, X He, K Feng, H Zhu - Agriculture, 2022 - mdpi.com
Traditional plant disease diagnosis methods are mostly based on expert diagnosis, which
easily leads to the backwardness of crop disease control and field management. In this …
easily leads to the backwardness of crop disease control and field management. In this …
Field detection of tiny pests from sticky trap images using deep learning in agricultural greenhouse
Agricultural pest catches on sticky traps can be used for the early detection and identification
of hotspots, as well as for estimating relative abundances of adult pests, occurring in …
of hotspots, as well as for estimating relative abundances of adult pests, occurring in …
A smartphone-based application for scale pest detection using multiple-object detection methods
Taiwan's economy mainly relies on the export of agricultural products. If even the suspicion
of a pest is found in the crop products after they are exported, not only are the agricultural …
of a pest is found in the crop products after they are exported, not only are the agricultural …
AI-based object detection latest trends in remote sensing, multimedia and agriculture applications
Object detection is a vital research direction in machine vision and deep learning. The object
detection technique based on deep understanding has achieved tremendous progress in …
detection technique based on deep understanding has achieved tremendous progress in …
Swin-MLP: A strawberry appearance quality identification method by Swin Transformer and multi-layer perceptron
Accurate identifying of strawberry appearance quality is an important step for robot picking in
the orchard. The convolutional neural network (CNN) has greatly helped the computer vision …
the orchard. The convolutional neural network (CNN) has greatly helped the computer vision …