Plant species identification accuracy is essential for ecological study, agricultural management, and biodiversity conservation. Conventional plant identification techniques are labor-intensive and prone to human error since they rely on manual inspection and specialist knowledge. Using advances in computer vision and deep learning, this project investigates the use of artificial intelligence (AI) to. Our convolutional neural network (CNN) model was created and trained on a wide range of leaf images that corresponded to different plant species. The architecture of the model was fine-tuned to accommodate changes in leaf color, texture, and shape, hence augmenting its capacity to generalize to diverse plant species. Pre-processing methods are used in our approach to enhance image quality, and data augmentation tactics are employed to strengthen the model's resilience.accurate species identification is critical for managing conservation projects and monitoring ecosystems, which is where automated plant identification can play a significant role in biodiversity conservation efforts. Additionally, these systems can help identify uncommon or endangered species, which helps to preserve and conserve them. Using ensemble models and attention processes, which enhance identification performance by concentrating on important regions of the leaf image, is another development (Rahman et al., 2020). Attention-guided CNNs are able to highlight specific leaf features, including vein structures or edges, which are important for identifying the type of plant. Furthermore, to improve resilience, ensemble methods that integrate predictions from various models or architectures have been suggested. Talk about how many parameters your model has, how much memory it needs, and how scalable it is for more datasets.Hardware prerequisites: Talk about the performance effects of the hardware (such as the GPU and CPU) used for testing and training to enhance the accuracy and dependability of the system. The goal of this project is to build a system that blends deep learning methods with leaf image analysis, so making a contribution to the expanding field of AI-based plant identification.
Convolutional Neural Network (CNN), Image Recognition, Species Classification, Artificial Intelligence, Plant Identification, Leaf Images
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