Python-Plant Leaf Identification Using Feature Fusion Wavelet Scattering Network CNN-MyProjectBazaar

Deep learning models, particularly Convolutional Neural Networks (CNNs), are pivotal inenabling botanists to efficiently identify plant species, which is essential for applications in medicine,agriculture, and the food industry. Unlike traditional machine learning methods that often struggle tocapture the intricate features of leaves, CNNs are well-suited for this task. However, their reliance onlarge datasets and substantial computational resources poses a significant challenge. To overcome thesechallenges, we present a new approach that combines features from Wavelet Scattering Networks (WSNs)and MobileNetV2. WSNs are particularly effective in capturing texture patterns using fixed filters that do notrequire a learning process, making them effective even with smaller datasets. Conversely, MobileNetV2 deeplayer features complement this by capturing more complex, high-level features like shapes and edges, whichare essential for distinguishing between different plant species. The extracted features are classified usinga PCA-based classifier, which reduces redundancy and enhances accuracy. We tested our approach on theFlavia and Folio datasets, achieving impressive accuracies of 98.75% and 98.7%, respectively. Additionally,we used the Cope dataset to assess the scalability of our model across different classes and the UK Leafdataset to evaluate its performance under varying background and noise conditions. This approach deliversgood accuracy while minimizing computational demands, providing a practical and efficient solution forautomated leaf classification, particularly in resource-constrained environments. Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577 Shop Now @ https://myprojectbazaar.com/ Get Discount @ Chat Now @ https://bit.ly/3rzVhHE Visit Our Channel: https://bit.ly/3rDLO24 Mail Us: [email protected]