Imagenet-hard: The hardest images remaining from a study of the power of zoom and spatial biases in image classification
Image classifiers are information-discarding machines, by design. Yet, how these models
discard information remains mysterious. We hypothesize that one way for image classifiers …
discard information remains mysterious. We hypothesize that one way for image classifiers …
Language-Driven Anchors for Zero-Shot Adversarial Robustness
Abstract Deep Neural Networks (DNNs) are known to be susceptible to adversarial attacks.
Previous researches mainly focus on improving adversarial robustness in the fully …
Previous researches mainly focus on improving adversarial robustness in the fully …
PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition
Deep learning-based object recognition systems can be easily fooled by various adversarial
perturbations. One reason for the weak robustness may be that they do not have part-based …
perturbations. One reason for the weak robustness may be that they do not have part-based …
Indian Traffic Sign Detection and Classification Through a Unified Framework
Traffic sign boards are vital in facilitating smart transportation systems. More than 90% of
accidents happen due to drivers' inattentiveness over these boards. Hence, relaying traffic …
accidents happen due to drivers' inattentiveness over these boards. Hence, relaying traffic …