Personal Project

PlantVision AI

PlantVision AI: Deep Learning Model for Plant Species Classification

2023New YorkPersonal Research Project

Developed a high-accuracy deep learning model using PyTorch for plant species classification, training on a dataset of over 40,000 plant images across 25 different species, achieving 95% accuracy in identification.

Technologies & Skills

PyTorch
Deep Learning
Computer Vision
Python
Neural Networks
Data Processing
Transfer Learning
GPU Computing

Project Objectives

  • Create a highly accurate plant species classification model
  • Process and prepare large-scale image dataset
  • Implement efficient training pipeline using GPU acceleration
  • Optimize model architecture for maximum accuracy

Key Achievements

  • Built and trained a custom CNN architecture using PyTorch
  • Processed and augmented dataset of 40,000+ plant images
  • Achieved 95% accuracy in species classification
  • Implemented transfer learning techniques for improved model performance
  • Developed data preprocessing pipeline for image standardization
  • Created robust validation methodology for model testing

Project Outcomes

  • Achieved 95% classification accuracy across 25 plant species
  • Successfully processed and utilized 40,000+ training images
  • Developed efficient data augmentation pipeline
  • Created scalable solution for plant species identification

Team Composition

  • Solo Project