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Found 3 papers, 1 papers with code
A Fine-Grained Image Description Generation Method Based on Joint Objectives
The goal of fine-grained image description generation techniques is to learn detailed information from images and simulate human-like descriptions that provide coherent and comprehensive textual details about the image content.
Comparative Evaluation of Recent Universal Adversarial Perturbations in Image Classification
Furthermore, we conduct a comprehensive evaluation of different loss functions within consistent training frameworks, including noise-based and generator-based.
Boosting Adversarial Transferability via Fusing Logits of Top-1 Decomposed Feature
Recent research has shown that Deep Neural Networks (DNNs) are highly vulnerable to adversarial samples, which are highly transferable and can be used to attack other unknown black-box models.
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