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Showing 1 to 20 of 39 for “"yield prediction"”.

  1. Applications of Machine Learning in Apple Crop Yield Prediction

    … of machine learning techniques to predict yield in the apple industry. Crop yield prediction is important because it impacts resource and capacity planning. It is, however, challenging because yield is affected by multiple interrelated factors such as climate conditions and orchard …

    cape-town Repository record for Applications of Machine Learning in Apple Crop Yield Prediction (opens in a new tab)

  2. Corn Yield Prediction Using Crop Growth and Machine Learning Models

    … while another area of interest includes yield prediction. Humidity, air and soil temperature, solar radiation, and wind speed are some key weather elements monitored in smart farms. We introduce a mechanistic crop growth model to predict crop growth and subsequent yield, subject to …

    ottawa-retro Repository record for Corn Yield Prediction Using Crop Growth and Machine Learning Models (opens in a new tab)

  3. Component-derived manufacturing yield prediction in circuit card design and assembly

    … defects and rework. To mitigate these costs, yield prediction analysis software is utilized to predict potential manufacturing defect rates and first pass yields of new designs. This thesis describes the creation and testing of a new data analysis model for yield prediction. By gathering and …

    mit Repository record for Component-derived manufacturing yield prediction in circuit card design and assembly (opens in a new tab)

  4. Generalizing yield prediction approaches and evaluating the common factors influencing the models

    Accurate crop yield prediction is one of the key areas in precision agriculture and it has been explored since the 1970s. This study integrates insights from three chapters, including a literature review and two experimental studies. These are used to evaluate how spatial resolution, the proximity …

    uiuc Repository record for Generalizing yield prediction approaches and evaluating the common factors influencing the models (opens in a new tab)

  5. A growth and yield prediction model for thinned stands of yellow- poplar

    … and evaluation of the simultaneous growth and yield equations presented by Beck and Della-Bianca (1972) for predicting basal area growth and cubic-foot volume growth and yield in yellow-poplar stands after a single thinning indicated that a separate set of coefficients was required for stands …

    vt Repository record for A growth and yield prediction model for thinned stands of yellow- poplar (opens in a new tab)

  6. A phenology-guided deep learning framework for advanced soybean yield prediction in the Americas

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01

    uiuc Repository record for A phenology-guided deep learning framework for advanced soybean yield prediction in the Americas (opens in a new tab)

  7. Supervised and self-supervised deep learning approaches for weed identification and soybean yield prediction

    … innovative solution to weed detection and crop yield prediction. The study focuses on key weed species: Italian ryegrass in wheat, Palmer amaranth, and common ragweed in soybean, which are troublesome weeds in the United States. One of the most innovative components of this research is the debut …

    vt Repository record for Supervised and self-supervised deep learning approaches for weed identification and soybean yield prediction (opens in a new tab)

  8. Generating a climatology of surface solar radiation over the UK with application to wheat yield prediction

    … of the variable radiation climate to the UK ‘yield plateau’ in wheat which has been widely observed over the last twenty years. Trend analyses do not support the theory that the observed yield plateau may be completely explained by solar radiation variability, since the main wheat growing area …

    east-anglia Repository record for Generating a climatology of surface solar radiation over the UK with application to wheat yield prediction (opens in a new tab)

  9. Using Remote Sensing and Machine Learning to Improve County-Level Crop Yield Prediction in the Us Corn Belt

    … and timely information about potential crop yield. Therefore, accurate and timely crop yield prediction is crucial, as it provides essential insights to the stakeholders. Consequently, large-scale crop yield prediction has recently garnered considerable attention. Despite the advancements in …

    alabama Repository record for Using Remote Sensing and Machine Learning to Improve County-Level Crop Yield Prediction in the Us Corn Belt (opens in a new tab)

  10. Evaluation of the UAV-Based Multispectral Imagery and Its Application for Crop Intra-Field Nitrogen Monitoring and Yield Prediction in Ontario

    … of RapidEye. Secondly, the nitrogen weight and yield in wheat was predicted using the UAV-based imagery. The intra-field nitrogen prediction model performs well at wheat early growth stage. Additionally, the best data collection time for yield prediction is at the end of booting stage. The …

    uwo Repository record for Evaluation of the UAV-Based Multispectral Imagery and Its Application for Crop Intra-Field Nitrogen Monitoring and Yield Prediction in Ontario (opens in a new tab)

  11. Semiconductor yield analysis and prediction using a stochastic layout sensitivity model

    … for enhancement of semiconductor manufacturing yield. As a result, the yield of modern integrated circuits is associated with the layout sensitivity to defects. The term layout sensitivity' is defined as the ratio of 'critical area', i.e. part of the layout in which a defect must be placed to …

    unm Repository record for Semiconductor yield analysis and prediction using a stochastic layout sensitivity model (opens in a new tab)

  12. Adapting Transformer Encoder Architecture for Continuous Weather Datasets with Applications in Agriculture, Epidemiology and Climate Science

    … small datasets, which is a bottleneck for many prediction tasks in agriculture, epidemiology, and climate science. Leveraging a novel pretraining dataset composed of 39 years of satellite measurements across the Americas, WeatherFormer achieves state-of-the-art performance in crop yield

    mit Repository record for Adapting Transformer Encoder Architecture for Continuous Weather Datasets with Applications in Agriculture, Epidemiology and Climate Science (opens in a new tab)

  13. Simulating the Soil Erosion from Land Removed from CRP

    … of this study was to calibrate an erosion prediction model and use it to estimate increased soil erosion due to this land use change. The Water Erosion Prediction Project (WEPP), a process based erosion prediction model developed by USDA, was utilized in this study for this purpose. Runoff …

    sdstate Repository record for Simulating the Soil Erosion from Land Removed from CRP (opens in a new tab)

  14. Towards a Strawberry Harvest Prediction System Using Computer Vision and Pattern Recognition

    … a time-series model of the field as a whole; and prediction, which uses the field’s history to guess when the most likely harvest window will be. The best method of data acquisition is determined through a decision matrix to be a small autonomous rover. Several challenges specific to images …

    calpoly Repository record for Towards a Strawberry Harvest Prediction System Using Computer Vision and Pattern Recognition (opens in a new tab)

  15. Millimeter-wave radar dataset for multi-modal fusion and keypoint detection in under-canopy soybean and corn row navigation

    … deep learning framework for radar-based keypoint prediction that leverages unprocessed range–azimuth radar data. The model employs knowledge distillation from a vision-based teacher network and fuses radar and camera features within an encoder–decoder architecture supervised by soft heatmap …

    uiuc Repository record for Millimeter-wave radar dataset for multi-modal fusion and keypoint detection in under-canopy soybean and corn row navigation (opens in a new tab)

  16. Remote sensing-based assessment of crop yield and water dynamics in the southern Great Plains (USA)

    … a crucial tool for estimating and understanding yield variability and water management in diverse cropping systems. This is particularly important in water-limited areas, such as the southern Great Plains, where water is the key to sustaining agricultural production. Therefore, the present …

    ksu Repository record for Remote sensing-based assessment of crop yield and water dynamics in the southern Great Plains (USA) (opens in a new tab)

  17. Optimizing yield and crop nitrogen response characterization by integrating spectral reflectance and agronomic properties in sugarcane and rice

    … and depth on red and red-edge reflectance based prediction models for biomass and grain yield in rice, 2) evaluate agronomic parameters of different sugar cane varieties in response to variable levels of nitrogen supply, and 3) determine the effect of sugarcane varieties on the relationships …

    lsu-thes Repository record for Optimizing yield and crop nitrogen response characterization by integrating spectral reflectance and agronomic properties in sugarcane and rice (opens in a new tab)

  18. Estimation of system assembly and test manufacturing yields through product complexity normalization

    … the ability to define appropriate manufacturing yield goals. Cisco's manufacturing operations can be divided, at a very high level, in two major steps: Printed Circuit Board Assembly (PCBA) and System Assembly and Test. The company has already deployed a global yield goal definition methodology …

    mit Repository record for Estimation of system assembly and test manufacturing yields through product complexity normalization (opens in a new tab)

  19. Diameter and height increment and mortality functions for loblolly pine trees in thinned and unthinned plantations

    … as to the benefits of individual tree growth and yield prediction models over stand-level models, individual tree models still have wide acceptance. A generalized thinning response variable which can account for the intensity of thinning, as well as the age of the stand at the time of thinning and …

    vt Repository record for Diameter and height increment and mortality functions for loblolly pine trees in thinned and unthinned plantations (opens in a new tab)

  20. Cancer risk prediction with next generation sequencing data using machine learning

    … detected with SAMtools and GATK achieve similar prediction accuracies. It is also noted that the features that are ranked with the PCC yield better accuracy than the chi-square test. In all of the analyses, the SNPs are identified to have superior accuracy as compared to the INDELs or the full …

    njit Repository record for Cancer risk prediction with next generation sequencing data using machine learning (opens in a new tab)

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