Results 11 to 20 of about 307,928 (266)

Multitask ST-LSTM model based on UAV hyperspectral remote sensing for wheat yield prediction [PDF]

Frontiers in Plant Science
Timely and accurate acquisition of wheat yield is essential for ensuring food security and improving breeding efficiency. However, temporal variation relationships across growth stages have not been fully exploited in existing wheat yield prediction ...
Yumeng Li, Chunying Wang, Chunying Wang, Junke Zhu, Qinglong Wang, Zengyue Li, Ping Liu, Ping Liu   +7 more
doaj   +2 more sources

Early Apple Yield Prediction Based on Flowering Stage Image Thinning Simulation Characteristics [PDF]

Plants
The existing fruit tree yield prediction methods mainly rely on fruit period images or long-term meteorological and soil data, which make it difficult to meet the needs of early yield prediction.
Qihang Yang, Liqun Liu
doaj   +2 more sources

Wheat Yield Prediction Using Unmanned Aerial Vehicle RGB-Imagery-Based Convolutional Neural Network and Limited Training Samples

Remote Sensing, 2023
Low-cost UAV RGB imagery combined with deep learning models has demonstrated the potential for the development of a feasible tool for field-scale yield prediction.
Juncheng Ma, Yongfeng Wu, Binhui Liu, Wenying Zhang, Bianyin Wang, Zhaoyang Chen, Guangcai Wang, Anqiang Guo   +7 more
doaj   +1 more source

When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges

Journal of Chemical Information and Modeling, 2023
Machine Learning techniques face significant challenges when predicting advanced chemical properties, such as yield, feasibility of chemical synthesis, and optimal reaction conditions. These challenges stem from the high-dimensional nature of the prediction task and the myriad essential variables involved, ranging from reactants and reagents to ...
Voinarovska, Varvara, Kabeshov, Mikhail, Dudenko, Dmytro, Genheden, Samuel, Tetko, Igor V.   +4 more
openaire   +4 more sources

County-level corn yield prediction using supervised machine learning

European Journal of Remote Sensing, 2023
The main objectives of this study are (1) to compare several machine learning models to predict county-level corn yield in the study area and (2) to compare the feasibility of machine learning models for in-season yield prediction.
Shahid Nawaz Khan, Abid Nawaz Khan, Aqil Tariq, Linlin Lu, Naeem Abbas Malik, Muhammad Umair, Wesam Atef Hatamleh, Farah Hanna Zawaideh   +7 more
doaj   +1 more source

When SMILES Smiles, Practicality Judgment and Yield Prediction of Chemical Reaction via Deep Chemical Language Processing

IEEE Access, 2021
Simplified Molecular Input Line Entry System (SMILES) provides a text-based encoding method to describe the structure of chemical species and formulize general chemical reactions.
Shu Jiang, Zhuosheng Zhang, Hai Zhao, Jiangtong Li, Yang Yang, Bao-Liang Lu, Ning Xia   +6 more
doaj   +1 more source

Predicting Table Beet Root Yield with Multispectral UAS Imagery

Remote Sensing, 2021
Timely and accurate monitoring has the potential to streamline crop management, harvest planning, and processing in the growing table beet industry of New York state.
Robert Chancia, Jan van Aardt, Sarah Pethybridge, Daniel Cross, John Henderson   +4 more
doaj   +1 more source

Yield Predict: A Crop Yield Prediction Framework for Smart Farms

International Journal of Advanced Research in Science, Communication and Technology, 2023
In today’s world the most important thing for living in the Indian economy is agriculture.In recent years, machine learning approaches are gaining popularity with the advent of big data. Adoption of these approaches in the agricultural sector has immense potential to increase crop productivity and quality.
null Shinde Shivnanda, null Pawar Nikita, null Dhage Tanaji   +2 more
openaire   +1 more source

Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields

Remote Sensing, 2020
Crop yield prediction prior to harvest is important for crop income and insurance projections, and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and predictor ...
Angela Kross, Evelyn Znoj, Daihany Callegari, Gurpreet Kaur, Mark Sunohara, David R. Lapen, Heather McNairn   +6 more
doaj   +1 more source

SlypNet: Spikelet-based yield prediction of wheat using advanced plant phenotyping and computer vision techniques

Frontiers in Plant Science, 2022
The application of computer vision in agriculture has already contributed immensely to restructuring the existing field practices starting from the sowing to the harvesting.
Arpan K. Maji, Sudeep Marwaha, Sudhir Kumar, Alka Arora, Viswanathan Chinnusamy, Shahnawazul Islam   +5 more
doaj   +1 more source