148_1000.jpg May 2026

The rise of deep learning relies on massive datasets where individual image quality and annotation accuracy are often assumed rather than verified.

1. Introduction

Generating Grad-CAM visualizations to identify which pixels the model focuses on when classifying this specific image. 3. Results & Discussion 148_1000.jpg

Summary of how individual data point audits can lead to more robust AI models.

To investigate the representational value of specific data points within the broader training set. 2. Methodology The rise of deep learning relies on massive

Using a pre-trained ResNet-50 or Vision Transformer (ViT) to extract the embedding vector for 148_1000.jpg .

Edge cases or "noisy" samples (like 148_1000.jpg ) can disproportionately affect model convergence or bias. 148_1000.jpg

Recommendations for automated "cleaning" of datasets based on high-loss samples.