Wildlife Image Data Labeler (Project): Camera trap image annotation for species classification
ImageClassification
During a wildlife monitoring project, I fine-tuned a ResNet50 model using manually labeled camera trap images. I was responsible for curating the training dataset of 8,000 images, creating class labels for three mammal species, and validating label accuracy using domain expert feedback. The labeling process was fundamental for the reliable performance of the image classifier.
• Hand-labeled thousands of images to support supervised model fine-tuning.
• Integrated class labels into the training pipeline for efficient processing.
• Coordinated with field researchers to verify label accuracy and relevance.
• Optimized labeled dataset for balanced class representation.
During a wildlife monitoring project, I fine-tuned a ResNet50 model using manually labeled camera trap images. I was responsible for curating the training dataset of 8,000 images, creating class labels for three mammal species, and validating label accuracy using domain expert feedback. The labeling process was fundamental for the reliable performance of the image classifier. • Hand-labeled thousands of images to support supervised model fine-tuning. • Integrated class labels into the training pipeline for efficient processing. • Coordinated with field researchers to verify label accuracy and relevance. • Optimized labeled dataset for balanced class representation.
2023 - 2023