Results 71 to 80 of about 10,061,248 (351)

Multispectral Crop Yield Prediction Using 3D-Convolutional Neural Networks and Attention Convolutional LSTM Approaches

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
In recent years, national economies are highly affected by crop yield predictions. By early prediction, the market price can be predicted, importing, and exporting plan can be provided, social, and economic effects of waste products can be minimized, and
Seyed Mahdi Mirhoseini Nejad, D. Abbasi-Moghadam, A. Sharifi, Nizom Farmonov, Khilola Amankulova, Mucsi Lászlź   +5 more
semanticscholar   +1 more source

Crop yield prediction in agriculture: A comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability

Heliyon
The agriculture sector is confronted with numerous challenges in the quest for accurate crop yield estimation, which is essential for efficient resource management and mitigating food scarcity in a rapidly growing global population.
M. Jabed, M. A. Azmi Murad
semanticscholar   +1 more source

Sweet corn yield prediction using machine learning models and field-level data

Precision Agriculture, 2023
The advent of modern technologies, acquisition of large amounts of crop management and weather data, and advances in computing are reshaping modern agriculture.
Daljeet S Dhaliwal, Martin M. Williams
semanticscholar   +1 more source

A Review of CNN Applications in Smart Agriculture Using Multimodal Data

Sensors
This review explores the applications of Convolutional Neural Networks (CNNs) in smart agriculture, highlighting recent advancements across various applications including weed detection, disease detection, crop classification, water management, and yield
Mohammad El Sakka, Mihai Ivanovici, Lotfi Chaari, Josiane Mothe   +3 more
doaj   +1 more source

Modeling of the Effect of Process Variations on a Micromachined Doubly-Clamped Beam

Micromachines, 2017
In the fabrication of micro-electro-mechanical systems (MEMS) devices, manufacturing process variations are usually involved. For these devices sensitive to process variations such as doubly-clamped beams, mismatches between designs and final products ...
Lili Gao, Zai-Fa Zhou, Qing-An Huang
doaj   +1 more source

A proposed framework for crop yield prediction using hybrid feature selection approach and optimized machine learning

Neural computing & applications (Print)
Accurately predicting crop yield is essential for optimizing agricultural practices and ensuring food security. However, existing approaches often struggle to capture the complex interactions between various environmental factors and crop growth, leading
Mahmoud Abdel-salam, Neeraj Kumar, Shubham Mahajan   +2 more
semanticscholar   +1 more source

Tackling Food Insecurity Using Remote Sensing and Machine Learning-Based Crop Yield Prediction

IEEE Access, 2023
Precise estimation of crop yield is crucial for ensuring food security, managing the supply chain, optimally utilizing resources, promoting economic growth, enhancing climate resilience, controlling losses, and mitigating risks in the agricultural ...
Uferah Shafi, Rafia Mumtaz, Zahid Anwar, Muhammad Ajmal, Muhammad Ajmal Khan, Zahid Mahmood, Dr. Maqsood Qamar, Hafiz Muhammad Jhanzab   +7 more
semanticscholar   +1 more source

Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US

Sensors
Efficient and reliable corn (Zea mays L.) yield prediction is important for varietal selection by plant breeders and management decision-making by growers.
Sayantan Sarkar, Javier M. Osorio Leyton, Efrain Noa-Yarasca, Kabindra Adhikari, Chad B. Hajda, Douglas R. Smith   +5 more
doaj   +1 more source

Accurate Wheat Yield Prediction Using Machine Learning and Climate-NDVI Data Fusion

IEEE Access
Due to exponential population growth, climate change, and an increasing demand for food, there is an unprecedented need for a timely, precise, and dependable assessment of crop yield on a large scale. Wheat, a staple crop worldwide, requires accurate and
Muhammad Ashfaq, Imran Khan, Abdulrahman Alzahrani, Muhammad Usman Tariq, Humera Khan, Anwar Ghani   +5 more
semanticscholar   +1 more source

Improving Generalisability and Transferability of Machine-Learning-Based Maize Yield Prediction Model Through Domain Adaptation

Social Science Research Network, 2023
Modern problems in agricultural management require non-traditional solutions, one of which is by utilizing domain adaptive machine learning models for crop yield prediction which are able to perform reliably in different temporal or spatial domains ...
R. Priyatikanto, Yang Lu, J. Dash, J. Sheffield   +3 more
semanticscholar   +1 more source