Data augmentation enhances model generalization in computer vision but may introduce biases, impacting class accuracy unevenly.

Data augmentation enhances model generalization in computer vision but may introduce biases, impacting class accuracy unevenly.

Data augmentation enhances model generalization in computer vision but may introduce biases, impacting class accuracy unevenly.

Data augmentation enhances model generalization in computer vision but may introduce biases, impacting class accuracy unevenly.

Data augmentation enhances model generalization in computer vision but may introduce biases, impacting class accuracy unevenly.

How to build a system that automatically detects and categorizes objects in media as soon as users upload it, storing the results in a database for future use.

This conclusion summarizes insights on how topology awareness affects GNN generalization performance.

This case study demonstrates the application of shortest-path distance to evaluate GNN performance on structural subgroups.

Explore the main results on GNN generalization performance, highlighting how structural distance affects accuracy disparities across subgroups.

Explore the relationship between topology awareness and generalization performance in GNNs using metric distortion.

Review the nature of topology awareness in GNNs, including its impact on generalization, and active learning challenges.

Explore the influence of topology awareness on the generalization performance of Graph Neural Networks (GNNs) in this comprehensive study.

Discover a framework that enhances GNN learning, enabling fair k-shot learning and fairness constraint for equitable predictive performance in structural groups

This appendix details the experimental setup, hardware, hyperparameters, and additional results confirming GNN performance and findings across datasets.

Modified greedy and sampling algorithms solve Eq. (6) in GNNs for the k-center problem, with a running time complexity of O(k) and O(kn) respectively.

Learn how GNNs exhibit unfair generalization when comparing test groups with significant structural distance differences.

Edge detection is fundamental in computer vision, allowing us to identify object boundaries within images

Explore the rise of multimodal AI, a new frontier in artificial intelligence that integrates text, images, audio, and video for a more holistic approach.

Explore the causes of GAN mode collapse, including catastrophic forgetting and discriminator overfitting, to enhance the diversity of AI-generated outputs.

Most people think self-driving cars will improve traffic and safety — but that may not be correct. Here are some traffic issues self-driving cars could cause.