Leaf Tracking, Counting and Occlusion in Plants Using Artificial Neural Networks

Learn how to implement leaf tracking, counting, and occlusion detection in plants through a conference talk from Data Science Conference Europe 2022. Dive into image processing techniques including preprocessing, enhancement, segmentation, feature extraction, and classification using artificial neural networks (ANN). Master supervised learning methods with detailed explanations of image preprocessing techniques specifically designed for plant analysis. Explore practical implementation aspects including data representation, tensor operations, data augmentation techniques like rotation and mirroring, and ocean filtering. Understand crucial concepts such as input shape parameters, training-validation splits, tensor slices, and convolution operations. Work with real datasets while learning how to properly structure and preprocess image data for plant analysis tasks. Gain hands-on experience with TensorFlow decorators, data augmentation using uniform distribution, and proper dataset organization for training, validation, and testing phases.