Deep learning in image-based plant phenoty**

KM Murphy, E Ludwig, J Gutierrez… - Annual Review of Plant …, 2024 - annualreviews.org
A major bottleneck in the crop improvement pipeline is our ability to phenotype crops quickly
and efficiently. Image-based, high-throughput phenoty** has a number of advantages …

Explainable deep learning in plant phenoty**

S Mostafa, D Mondal, K Panjvani, L Kochian… - Frontiers in Artificial …, 2023 - frontiersin.org
The increasing human population and variable weather conditions, due to climate change,
pose a threat to the world's food security. To improve global food security, we need to …

Deep transfer learning based rice plant disease detection model.

RP Narmadha, N Sengottaiyan… - … Automation & Soft …, 2022 - search.ebscohost.com
In agriculture, plant diseases are mainly accountable for reduction in productivity and leads
to huge economic loss. Rice is the essential food crop in Asian countries and it gets easily …

[HTML][HTML] A comprehensive review of 3D convolutional neural network-based classification techniques of diseased and defective crops using non-UAV-based …

N Noshiri, MA Beck, CP Bidinosti, CJ Henry - Smart Agricultural Technology, 2023 - Elsevier
Hyperspectral imaging (HSI) is a non-destructive and contactless technology that provides
valuable information about the structure and composition of an object. It has the ability to …

[HTML][HTML] A systematic review of open data in agriculture

J Chamorro-Padial, R García, R Gil - Computers and Electronics in …, 2024 - Elsevier
In this work, we perform a systematic literature review of Open Data and Public Domain
datasets in Agriculture. We use the PRISMA method to analyze the existing academic …

[HTML][HTML] EasyIDP: A python package for intermediate data processing in UAV-based plant phenoty**

H Wang, Y Duan, Y Shi, Y Kato, S Ninomiya, W Guo - Remote Sensing, 2021 - mdpi.com
Unmanned aerial vehicle (UAV) and structure from motion (SfM) photogrammetry
techniques are widely used for field-based, high-throughput plant phenoty** nowadays …

Standardizing and centralizing datasets for efficient training of agricultural deep learning models

A Joshi, D Guevara, M Earles - Plant Phenomics, 2023 - spj.science.org
In recent years, deep learning models have become the standard for agricultural computer
vision. Such models are typically fine-tuned to agricultural tasks using model weights that …

Automatic detection and classification of disease in citrus fruit and leaves using a customized CNN based model

PJ Shermila, A Victor, SO Manoj… - … Latinoamericano y del …, 2024 - blacpma.ms-editions.cl
El avance y desarrollo comercial de India dependen en gran medida de la agricultura. Un
tipo de fruta comunmente cultivada en entornos tropicales es el cítrico. Se requiere un juicio …

[PDF][PDF] A novel framework for multi-classification of guava disease

O Almutiry, M Ayaz, T Sadad, IU Lali… - … , Materials & Continua, 2021 - academia.edu
Guava is one of the most important fruits in Pakistan, and is gradually boosting the economy
of Pakistan. Guava production can be interrupted due to different diseases, such as …

Visualizing feature maps for model selection in convolutional neural networks

S Mostafa, D Mondal, M Beck… - Proceedings of the …, 2021 - openaccess.thecvf.com
Convolutional neural networks (CNN) are increasingly being used to achieve state-of-the-art
performance for various plant phenoty** and agricultural tasks. While constructing such …