Machine learning in agriculture: a review of crop management applications

I Attri, LK Awasthi, TP Sharma - Multimedia Tools and Applications, 2024 - Springer
Abstract Machine learning has created new opportunities for data-intensive study in
interdisciplinary domains as a result of the advancement of big data technologies and high …

Detection and assessment of the spatio-temporal land use/cover change in the Thai Binh province of Vietnam's Red River delta using remote sensing and GIS

BB Thien, VT Phuong, DTV Huong - Modeling Earth Systems and …, 2023 - Springer
The land is one of the prime natural resources of a country, and its transformation is a
natural process that cannot be stopped but can be regulated. The issues of land use change …

Derin Evrişimli Sinir Ağları Kullanılarak Pirinç Hastalıklarının Sınıflandırılması

E Vezıroglu, I Pacal, A Coşkunçay - … of the Institute of Science and …, 2023 - dergipark.org.tr
Çeltik, temel bir gıda kaynağıdır ve endüstride sıkça kullanılan nadir bitkilerden biridir. Çeltik
yaprak hastalıklarının erken teşhisi, ekin hasarını en aza indirmek için büyük önem …

Deep residual CNN with contrast limited adaptive histogram equalization for weed detection in soybean crops

VS Babu, NV Ram - Traitement du Signal, 2022 - search.proquest.com
Weeding is the fundamental task in agriculture to increase yields crop. Accurate weed
recognition is major prerequisite in precision agriculture. Precision weeding significant …

[PDF][PDF] Papaya fruit maturity estimation using wavelet and ConvNET

AK Ratha, NK Barpanda, PK Sethy… - Journal homepage: http …, 2023 - academia.edu
The papaya (Carica papaya L.) is a tropical fruit with high commercial value due to its
superior nutritional and therapeutic properties. Papayas must be packaged in the fruit …

[PDF][PDF] Weed Detection in Soybean Crop Using Deep Neural Network.

V Singh, MK Gourisaria, H GM… - Pertanika Journal of …, 2023 - journals-jd.upm.edu.my
The problematic and undesirable effects of weeds lead to degradation in the quality and
productivity of yields. These unacceptable weeds are close competitors of crops as they …

Weed identification in broomcorn millet field using segformer semantic segmentation based on multiple loss functions

Z BI, Y LI, J GUAN, J LI, P ZHANG, X ZHANG… - … Environment and Food, 2024 - jstage.jst.go.jp
Computer vision and deep learning are one of the main technologies for weed intelligent
recognition in farmland. However, when using the deep learning technology to identify …

[PDF][PDF] Machine learning in agriculture for crop diseases identification: a survey

H Kukadiya, DD Meva - Int J Res GRANTHAALAYAH, 2023 - academia.edu
The field of computer science known as machine learning is used to create algorithms that
have the ability to self-learn or learn on their own. This is how the phrase" Machine …

Coastal wetlands of Indus River Delta are under risk due to reclamation: A spatiotemporal analysis during the past 50 years from 1972 to 2022

Y Laghari, S Bai, SJ Leghari, W Wei, AH Laghari - 2023 - researchsquare.com
Coastal wetlands are the most productive and biologically diverse ecosystems, benefiting
both human populations and the total environment. However, they are continuously …

Deep Learning Techniques for Green on Green Weed Detection from Imagery

MS Hasan - 2024 - researchportal.murdoch.edu.au
Weed is a major problem faced by the agriculture and farming sector. Advanced imaging
and deep learning (DL) techniques have the potential to automate various tasks involved in …