Results 231 to 240 of about 74,098 (264)

Crop species classification: A phenology based approach

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
We investigated the use of phenological information extracted from satellite imagery and supported by agro-ecological zoning (AEZ) in accurate crop classification and monitoring. Vegetation indices extracted from Landsat 8 imagery are capable to track the vegetation development through the year and from them the phenological profile can be extrapolated
Luciani, R., Laneve, G., Jahjah, M., OMULLOH, COLLINS MITTO   +3 more
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Crops Classification with Recommendation System

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Kalyani Chaudhari, Vaishnavi Warade, Nikita Shinde, Hema Darne, Mansi Rokade   +4 more
openaire   +1 more source

Fusing 3D information for crop/weeds classification

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002
The main goal of this work is to construct a 3D-world map to help to distinguish between crop and weeds and finally to permit the location of crop and weeds to apply a variable treatment. To solve the problem of recovering a 3D-local map, we use a motion technique with the possibility of changing zoom. Every independent local map will be fused into the
A. J. Sánchez, John A. Marchant
openaire   +2 more sources

Object-Based Postprocessing Method for Crop Classification MAPS

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
In this paper, we propose a novel method for an object-based post-classification filtering, specifically tailored to improve agricultural land use maps. That has significant impact on the solving other applied tasks like detection of land cover changes and crop rotation violation, area estimation and crop yield forecasting. The main idea of this method
Lavreniuk, Mykola, Kussul, Nataliia, Shelestov, Andrii, Dubovyk, Olena, Low, Fabian   +4 more
openaire   +2 more sources

Wavelet-based crop detection and classification

2010 18th Iranian Conference on Electrical Engineering, 2010
The worldwide problem of environmental pollution caused by excessive use of herbicides and the increasing cost of chemicals necessitates finding alternative methods for crop protection. In order to reduce the quantities of herbicides applied to fields, we propose to exploit the advantages of image processing to automatically detect and localize the ...
Sajad Kiani, Zohreh Azimifar, Saadat Kamgar   +2 more
openaire   +1 more source

Crop Classification on Deep Learning

2022 IET International Conference on Engineering Technologies and Applications (IET-ICETA), 2022
Ke-Hao Chen, Chiu-Chin Lin, Chung-Hsien Chen, Jen-Chun Lee, Chia-Ti Wu   +4 more
openaire   +1 more source

Crop Disease Auto-localization and Classification

2022
G. Deepank, Shivani Bisht, Aditya Verma, R. Tharun Raj, R. Jyothi   +4 more
openaire   +2 more sources

Deep hybrid classification model for leaf disease classification of underground crops

Web Intelligence
Underground crop leave disease classification is the most significant area in the agriculture sector as they are the significant source of carbohydrates for human food. However, a disease-ridden plant could threaten the availability of food for millions of people.
R. Salini, G. Charlyn Pushpa Latha, Rashmita Khilar   +2 more
openaire   +1 more source

Leaf images classification for the crops diseases detection

Multimedia Tools and Applications, 2022
Yashwant Kurmi, Suchi Gangwar, Vijayshri Chaurasia, Aditya Goel   +3 more
openaire   +1 more source

Classification of Agriculture Crops Using Transfer Learning

2022 OITS International Conference on Information Technology (OCIT), 2022
Silky Goel, Snigdha Markanday, Shlok Mohanty   +2 more
openaire   +2 more sources