Integration of computer vision for smart agriculture: Fundamentals and applications

Few-shot image classification of crop diseases based on vision–language models

10.3390/s24186109 · doi-reference

Estimating the growth indices and nitrogen status

10.3389/fpls.2021.619522 · doi-reference

Deep learning based automatic grape downy mildew detection

10.3389/fpls.2022.872107 · doi-reference

Cherry recognition in natural environment based on the vision of picking robot

10.1088/1755-1315/61/1/012021 · doi-reference

Using HJ-CCD image and PLS algorithm to estimate the yield of field-grown winter wheat

10.1038/s41598-020-62125-5 · doi-reference

Deep learning and computer vision in plant disease detection: a comprehensive review of techniques, models, and trends in precision agriculture

10.1007/s10462-024-11100-x · doi-reference

UAV imagery coupled deep learning approach for the development of an adaptive in-house web-based application for yield estimation in citrus orchard

10.1016/j.measurement.2024.114786 · doi-reference

Transformation of Indian agriculture through mechanization

10.30954/0424-2513.2.2019.4 · doi-reference

A contextualized approach for segmentation of foliage in different crop species

10.1016/j.compag.2018.11.033 · doi-reference

Yield estimation and visualization solution for precision agriculture

10.3390/s21196657 · doi-reference

Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment

10.1007/s11947-011-0725-1 · doi-reference

Real-time recognition of spraying area for UAV sprayers using a deep learning approach

10.1371/journal.pone.0249436 · doi-reference

Picking dynamic analysis for robotic harvesting of Agaricus bisporus mushrooms

10.1016/j.compag.2021.106145 · doi-reference

A computer-vision-based approach for nitrogen content estimation in plant leaves

10.3390/agriculture11080766 · doi-reference

IoT-based smart irrigation systems: An overview on the recent trends on sensors and IoT systems for irrigation in precision agriculture

10.3390/s20041042 · doi-reference

Drone-computer communication based tomato generative organ counting model using YOLO V5 and deep-sort

10.3390/agriculture12091290 · doi-reference

UAV imagery, advanced deep learning, and YOLOv7 object detection model in enhancing citrus yield estimation

10.21603/2308-4057-2025-2-650 · doi-reference

Applications of computer vision in plant pathology: a survey

10.1007/s11831-019-09324-0 · doi-reference

Deep learning assisted real-time nitrogen stress detection for variable rate fertilizer applicator in wheat crop

10.1016/j.compag.2025.110545 · doi-reference

Identifying crop water stress using deep learning models

10.1007/s00521-020-05325-4 · doi-reference

Deep learning approaches and interventions for futuristic engineering in agriculture

10.1007/s00521-022-07744-x · doi-reference

Fuzzy-IoT smart irrigation system for precision scheduling and monitoring

10.1016/j.compag.2023.108407 · doi-reference

Agricultural robots for field operations: concepts and components

10.1016/j.biosystemseng.2016.06.014 · doi-reference

Adaptive fault-tolerant control for pure-feedback stochastic nonlinear systems with sensor and actuator faults

10.1007/s00034-023-02366-7 · doi-reference

Computer vision based fruit grading system for quality evaluation of tomato in agriculture industry

10.1016/j.procs.2016.03.055 · doi-reference

Application, adoption and opportunities for improving decision support systems in irrigated agriculture: A review

10.1016/j.agwat.2021.107161 · doi-reference

A mobile-based system for detecting plant leaf diseases using deep learning

10.3390/agriengineering3030032 · doi-reference