Plant Specie Recognition

Plant species recognition aims to automatically identify plant species from images, leveraging advancements in computer vision and machine learning. Current research focuses on improving the accuracy and efficiency of deep learning models, particularly convolutional neural networks (CNNs) like ResNet, Inception, and Xception, often incorporating techniques such as transfer learning and novel pooling layers to better capture spatial features within plant images. Challenges include handling noisy user-generated data, addressing class imbalances in datasets, and optimizing model architectures for speed and resource efficiency. Improved plant recognition has significant implications for biodiversity monitoring, agricultural applications (e.g., disease detection), and botanical research.