Detección y conteo de plantas de palma mediante YOLO usando imágenes de dron (Proyecto de tesis SIG)

@dissanayakepvt

Hello, I am experienced in developing computer vision models using YOLO for agricultural applications. I can assist with dataset preparation, model training, and generating geospatial outputs in CSV or GeoJSON formats. My approach will ensure the model achieves the desired precision (≥85% mAP) and provide thorough documentation for reproducibility. I have worked with drone imagery and understand the agricultural context, ensuring effective results. If this aligns with your needs, I’d be glad to discuss details and start right away. Best regards, Sujeewa, GISPromo IT Solutions

@Muhammadzeesha59

As a highly accomplished Senior Full Stack Developer with six years of professional experience, I am able to bring a unique set of skills that are tailor-made for your project. My expertise spans a wide range of areas including Deep Learning, Image Processing, Machine Learning (ML), and Python, which directly aligns with your needs for developing your computer vision model to accurately identify and count oil palm plants via drone images. I have already worked on similar projects where aerial or drone imagery in agriculture was utilized for analysis and I delivered exceptional results. This invaluable experience enables me to fully understand the context and complexities you may face as an agronomist during the completion of your thesis. Additionally, my M.L skills will contribute to ensuring that the model achieves the desired accuracy level and metrics stipulated by your project. By tapping into my extensive knowledge in Java, Python, and other relevant programming languages, I'll be actively involved in preparing/validation of datasets for training, fine-tuning and training of the detection model, generating actionable insights in SIG compatible formats such as CSV, GeoJSON or Shapefile. Furthermore, I assure you value-adding deliverables including the trained model. Let's position ourselves academically and practically in a leading role through this project. (I'm aware my previous pitch was incomplete, so I resubmitted an updated pitch)

@sf264

Hello client, I am willing to develop a computer vision model that will be capable of detecting and counting oil palm plants from RGB images obtained with a drone. I have a vast experience in working with aerial and drone images in agriculture and forestry. By choosing me, you are choosing a partner that not only speaks, but delivers results that speak for themselves. Please message me so that we discuss your project requirements in more detail. Looking forward to contributing to your project success, Fahad.

@merinsinha

I can do it. As 9+ years experiences in these field. I can give good quality work. I have read the guidelines of your work.I believe that i can provide you the best quality works you are anticipating from this platform give me a chance to show you the best i can do at your service.

@toriquldev123

Hello Dear! I write to introduce myself. I'm Engineer Toriqul Islam. I was born and grew up in Bangladesh. I speak and write in English like native people. I am a B.S.C. Engineer of Computer Science & Engineering. I completed my graduation from Rajshahi University of Engineering & Technology ( RUET). I love to work on Web Design & Development project. Web Design & development: I am a full-stack web developer with more than 10 years of experience. My design Approach is Always Modern and simple, which attracts people towards it. I have built websites for a wide variety of industries. I have worked with a lot of companies and built astonishing websites. All Clients have good reviews about me. Client Satisfaction is my first Priority. Technologies We Use: Custom Websites Development Using ======>Full Stack Development. 1. HTML5 2. CSS3 3. Bootstrap4 4. jQuery 5. JavaScript 6. Angular JS 7. React JS 8. Node JS 9. WordPress 10. PHP 11. Ruby on Rails 12. MYSQL 13. Laravel 14. .Net 15. CodeIgniter 16. React Native 17. SQL / MySQL 18. Mobile app development 19. Python 20. MongoDB What you'll get? • Fully Responsive Website on All Devices • Reusable Components • Quick response • Clean, tested and documented code • Completely met deadlines and requirements • Clear communication You are cordially welcome to discuss your project. Thank You! Best Regards, Toriqul Islam

@techsty2014

Hello, I can assist you in developing a robust YOLO-based model to detect and count oil palm plants from drone-acquired RGB images. With experience in computer vision applied to agriculture, I will ensure your dataset is prepared and validated for training. I'll fine-tune the model, generate inferences on new images, and provide results in SIG-compatible formats like CSV or GeoJSON. I will deliver a trained model, Python scripts for training and inference, and a README with installation and execution instructions. Model metrics such as Precision, Recall, and mAP will be documented, ensuring the model meets the ≥85% mAP benchmark for accuracy. Questions: • Do you have a preference between YOLOv5 or YOLOv8, or are you open to recommendations based on dataset specifics? • Are there specific environmental conditions or image resolutions to consider during model training? I am excited to contribute to your thesis project by implementing best practices in computer vision and helping you achieve accurate and reliable results for agronomic analysis. Thanks and best regards, Faizan

@Web1devloper

As an experienced Data Analyst and Scientist, I believe I can offer you the unique blend of skills and insightful solutions needed to complete your geospatial analysis project focused on drone-collected palm plantation data. My 8+ years of experience in data analytics and Python-based Machine Learning arms me with a robust skillset to tackle a broad range of tasks, from data preparation to model training and generating reports that align with your needs. In particular, my expertise in computer vision –including YOLOv5 and similar architectures– perfectly matches your requirement of developing a computer vision model for palm tree detection in the aerial images collected by drones. Moreover, I bring an added advantage as I'm well-versed in widely-used geospatial tools like ArcGIS and QGIS that will enable me to seamlessly assist you with the results exports — be it CSV coords, GeoJSONs or shapefiles. Lastly, my communication skills and knack for translating complex findings into actionable insights complement my technical prowess - a key aspect to effectively collaborating when working remotely. Let’s leverage my proficiency to develop effective agricultural analytic solutions that truly advances your master's thesis research ambitions!

@eduvid

Hola, saludos cordiales, en la actualidad cuento con más de 15 años de experiencia trabajando en proyectos similares utilizando PYTHON, soy la persona ideal para cumplir al 100% sus requerimientos, no dude en escribirme :)

@draganm59

Estimado Employer, Estoy entusiasmado de poder ofrecer mi experiencia para su proyecto de detección y conteo de plantas de palma mediante YOLO. Con un sólido trasfondo en visión computacional y aprendizaje profundo, he trabajado extensamente en proyectos de detección de objetos utilizando arquitecturas YOLO, y mi experiencia se alinea perfectamente con sus necesidades de análisis agrícola y generación de información geoespacial. Entiendo la importancia de contar con un modelo preciso y eficiente para su investigación de tesis en Sistemas de Información Geográfica. Mi enfoque comienza con la preparación y validación del conjunto de datos, asegurando que las imágenes capturadas por dron sean optimizadas para el entrenamiento del modelo. Utilizaré YOLOv5 o YOLOv8, justificando la elección según las características específicas de sus imágenes y objetivos. Tras el entrenamiento y ajuste del modelo, generaré inferencias detalladas y exportaré los resultados en formatos compatibles con SIG, como CSV y GeoJSON, para facilitar su posterior uso en ArcGIS/QGIS. Además, proporcionaré documentación clara del flujo de trabajo, asegurando que pueda reproducir y adaptar el modelo según sea necesario. Mi experiencia previa en imágenes aéreas para aplicaciones agrícolas me permite entender los desafíos únicos que presenta este tipo de datos, asegurando que los resultados sean precisos y útiles para su análisis agronómico. Estoy comprometido en alcanzar una precisión ≥85% mAP para satisfacer sus expectativas y garantizar un flujo de inferencia robusto. Espero tener la oportunidad de colaborar con usted en este proyecto innovador y contribuir al éxito de su investigación. Atentamente, Dragan M.

@rogelitoc

Hello, I appreciate the opportunity to assist with your project focused on developing a computer vision model for counting oil palm plants using drone imagery. I understand the importance of achieving high accuracy in detection for agricultural analysis and geospatial information generation. With a strong background in agronomy and experience in implementing machine learning models, particularly using YOLO architectures, I am well-equipped to support your thesis project. My expertise includes data preparation, model training, and evaluation metrics, all vital for your needs. To ensure we meet your objectives, I propose the following approach: - Validate and prepare the dataset you provide to ensure optimal training conditions. - Train the detection model using YOLOv5 or YOLOv8, focusing on fine-tuning for improved accuracy. - Generate inferences on new images and export results in the required formats (CSV, GeoJSON, or shapefile). - Document the workflow thoroughly, providing clear installation and execution instructions. I am eager to start this project and am confident that I can deliver a model that meets your accuracy requirements. I would love to discuss any further details and can begin immediately. Looking forward to your response!

@ahmedf149

Hola, Soy un desarrollador full stack con experiencia práctica en visión artificial y proyectos de aprendizaje automático orientados a SIG. He realizado trabajos de detección de objetos utilizando arquitecturas basadas en YOLO para imágenes aéreas en agricultura y análisis ambiental. La solución proporcionará una validación adecuada de conjuntos de datos, revisión de anotaciones y preparación adaptada a imágenes RGB de drones. Proporcionaré capacitación y ajuste de un modelo YOLO con una configuración técnicamente justificada para lograr una alta precisión de detección. Si surgen problemas de desequilibrio de clases, sobreajuste o detecciones falsas, aplicaré soluciones específicas como aumento, ajuste de parámetros y estrategias de validación. Mi amplia experiencia incluye la generación de resultados de inferencia y la exportación de resultados a formatos compatibles con SIG para flujos de trabajo de ArcGIS y QGIS. El resultado final satisfará sus requisitos académicos con un modelo entrenado, scripts, métricas y documentación clara para su replicación. Atentamente, Ahmed

@artemb35

Hi there, I understand that your main goal is to develop an efficient detection and counting system for palm plants using YOLO with drone images for your thesis project. I have previously implemented a similar computer vision project that utilized YOLO to accurately detect and classify agricultural crops, resulting in a 95% accuracy rate. Additionally, my experience with image processing and drone technology has enabled me to optimize data collection methods, significantly reducing processing time. To meet your project requirements, I will create a customized YOLO model trained specifically on your palm plant images, ensuring high accuracy in detection and counting. I will also set up a streamlined workflow for processing drone images, allowing for efficient data analysis and visualization. I would be happy to discuss your needs and get started right away. Best regards, Artem

@hercluesn

Hello. I am an experienced computer vision engineer with expertise in YOLO-based object detection and agricultural drone imagery. I propose to develop a robust detection model for oil palm plants using your RGB drone images, ensuring outputs are compatible with GIS platforms such as ArcGIS and QGIS. The workflow will include dataset validation, data augmentation, model training, hyperparameter tuning, and performance evaluation (Precision, Recall, mAP). I will provide a Python-based script for both training and inference, along with clear instructions for reproducibility. The model will be trained to achieve a target mAP of ≥85% for reliable plant detection. Outputs will be exported in CSV, GeoJSON, or shapefile formats to facilitate spatial analysis. Documentation will include setup instructions, workflow explanation, and evaluation metrics to support your thesis work. I am committed to following best practices in computer vision, ensuring that the model is efficient, scalable, and easily integrated into your agricultural analysis pipeline. Regards, Justin.

@vlaso

I have solid hands-on experience building YOLO-based object detection pipelines (YOLOv5 / YOLOv8) for aerial and drone imagery, including agricultural and forestry use cases. I understand the full academic + applied workflow you’re aiming for—not just training a model, but producing reproducible, GIS-ready outputs that actually make sense in ArcGIS/QGIS. Here’s how I’d help: Validate and structure your RGB drone dataset (tiling, annotations, augmentation). Select and justify the best YOLO architecture for palm detection. Train and fine-tune the model with clear evaluation (Precision, Recall, mAP). Build clean Python scripts for training and inference. Export detections to CSV / GeoJSON / Shapefile with correct coordinates. Provide a clear README + workflow documentation for thesis reproducibility. I’m comfortable working in an academic context and collaborating without crossing into “doing the thesis.” Happy to discuss your dataset, GSD, flight height, and annotation format to get started

@guidoo25

Hola como estas tengo amplia experiencia en este tema tengo un modelo que detecta enfermedades comunes en plantaciones de cacao con segmentación y cuenta las mazorcas escríbeme para poder hablar mas detalle del tema.