A review of deep learning techniques used in agriculture
I Attri, LK Awasthi, TP Sharma, P Rathee - Ecological Informatics, 2023 - Elsevier
Deep learning (DL) is a robust data-analysis and image-processing technique that has
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
Advancing precision agriculture: The potential of deep learning for cereal plant head detection
Cereal plant heads must be identified precisely and effectively in a range of agricultural
applications, including yield estimation, disease detection, and breeding. Traditional …
applications, including yield estimation, disease detection, and breeding. Traditional …
[HTML][HTML] Global wheat head detection 2021: An improved dataset for benchmarking wheat head detection methods
Abstract The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has
assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various …
assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various …
Winter wheat yield prediction using convolutional neural networks from environmental and phenological data
Crop yield forecasting depends on many interactive factors, including crop genotype,
weather, soil, and management practices. This study analyzes the performance of machine …
weather, soil, and management practices. This study analyzes the performance of machine …
[PDF][PDF] Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives
Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of
genomics and environment on plants, limiting the progress of smart breeding and precise …
genomics and environment on plants, limiting the progress of smart breeding and precise …
Quick and accurate monitoring peanut seedlings emergence rate through UAV video and deep learning
Y Lin, T Chen, S Liu, Y Cai, H Shi, D Zheng… - … and Electronics in …, 2022 - Elsevier
During the seedling stage, real-time monitoring and detection of seed germination are
important for testing the quality of seeds, crop field management, and yield estimation …
important for testing the quality of seeds, crop field management, and yield estimation …
Field rice panicle detection and counting based on deep learning
X Wang, W Yang, Q Lv, C Huang, X Liang… - Frontiers in plant …, 2022 - frontiersin.org
Panicle number is directly related to rice yield, so panicle detection and counting has always
been one of the most important scientific research topics. Panicle counting is a challenging …
been one of the most important scientific research topics. Panicle counting is a challenging …
A sheep dynamic counting scheme based on the fusion between an improved-sparrow-search YOLOv5x-ECA model and few-shot deepsort algorithm
Y Cao, J Chen, Z Zhang - Computers and Electronics in Agriculture, 2023 - Elsevier
In order to improve the accuracy of sheep counting and avoid the interference of mutual
occlusion caused by different moving speed among sheep, the concept of fusion between …
occlusion caused by different moving speed among sheep, the concept of fusion between …
Disruptive technologies in smart farming: an expanded view with sentiment analysis
Smart Farming (SF) is an emerging technology in the current agricultural landscape. The
aim of Smart Farming is to provide tools for various agricultural and farming operations to …
aim of Smart Farming is to provide tools for various agricultural and farming operations to …
Wheat ear recognition based on RetinaNet and transfer learning
J Li, C Li, S Fei, C Ma, W Chen, F Ding, Y Wang, Y Li… - Sensors, 2021 - mdpi.com
The number of wheat ears is an essential indicator for wheat production and yield
estimation, but accurately obtaining wheat ears requires expensive manual cost and labor …
estimation, but accurately obtaining wheat ears requires expensive manual cost and labor …