Introduction to Image Classification and Object Detection in Agriculture and Natural Sciences

This two-day workshop, Introduction to Image Classification and Object Detection in Agriculture and Natural Sciences with R and Python (27–28 November 2025, led by Reza Belaghi), offers participants both conceptual foundations and hands-on experience in applying AI and machine learning to image data.

Day 1 covers core concepts of supervised and unsupervised learning, deep learning, and computer vision, with a focus on image classification methods (CNN, ANN) and pretrained architectures (ResNet, DenseNet, EfficientNet), as well as object detection approaches such as YOLO, Faster R-CNN, and SSD, demonstrated in both R and Python.

Day 2 emphasizes practice through guided coding sessions, including preprocessing, model training and fine-tuning, evaluation, and real-world applications on datasets from agriculture, medicine, and open sources. Participants will gain practical skills in implementing and comparing R and Python solutions while also engaging in discussions on real-world challenges, limitations, and some of ethical considerations of machine learning in agricultural and natural sciences.