Existing research mainly focuses on multi-class classification models ... single-label adversarial attacks and stimulate more interest in the multi-label adversarial attack problem. Abstract: ...

Instead, multiple metrics exist, each assessing a different aspect of the classification process, and these metrics are often inconsistent with one another. Consequently, multi-label feature selection ...

More concretely, the dataset contains 122,218 images and covers 80 common categories (class 81 is background). For multi-label image classification, MS COCO is further divided into a training set of ...

In this paper, we investigate efficient annotation strategies for collecting multi-class classification labels fora large collection of images ... view annotation as a semi-supervised learning problem ...

In the research, they analyze the two challenges of learning from time series data with noisy labels: (a) Label noise in time ...

The FDA's rule proposal would, if finalized, require U.S. food manufacturers to add a front-of-package (FOP) nutrition label on most packaged food goods produced in the United States. Related ...

X is further aiming to clamp down on impersonation by rolling out a label for parody accounts to ... it's unlikely to meaningfully target the problem of impersonation. Scammers who impersonate ...

This paper aims to improve the feature diversity of training samples while expanding the data scale by mixing the locally ...