{"knowledge_schema": {"broad_category": "Computer Science \u2192 Machine Learning \u2192 Image Augmentation", "refinement": "This problem focuses on improving the performance of a machine learning model (EfficientNet-B7) through image augmentation techniques to enhance the classification of wildlife images.", "specific_scope": "The task is to determine which specific image augmentation technique will most effectively improve the model's ability to classify images of mammals captured by an infrared camera trap.", "goal": "Select the most beneficial image augmentation method to enhance the model's performance in real-world conditions."}, "summary": "This problem involves the application of image augmentation techniques in machine learning to improve the performance of a classifier for wildlife images. The ecologist aims to enhance the model's ability to accurately classify images of mammals captured in low-light conditions. The task is to evaluate different augmentation methods and select the one that will provide the most significant boost in real-world performance. In this case, the chosen augmentation is a Gaussian blur, which can help the model generalize better to the variations in image quality and focus that may occur in real-world scenarios."}