Abstract: Clothing attribute recognition, especially in unconstrained street images, is a challenging task for multimedia. Existing methods for multi-task clothing attribute prediction often ignore ...
Abstract: The network with attributes at the nodes is called an attribute network. Detecting abnormal nodes in the attribute network has a wide range of applications in real life, such as detecting ...
A simulation study is designed to explore the accuracy of attribute parameter estimation in the crossed random effects linear logistic test model (CRELLTM) with the impact of Q-matrix misspecification ...
This paper presents an approach based on quality attribute (QA) scenarios to elicit and define system- and model-relevant test cases for ML models. Testing of machine learning (ML) models is a known ...
Setting the serialize_as_any parameter for the BaseModel.model_dump[_xxx]() methods to True causes an error to be thrown on all models that have a recursive attribute ...
Attribute reduction is a research hotspot in rough set theory. Traditional heuristic attribute reduction methods add the most important attribute to the decision attribute set each time, resulting in ...
Over the years, the Spring Framework has continually evolved its support for annotations, meta-annotations, and composed annotations. This document is intended to aid developers (both end users of ...
Sparsity is becoming arguably the most critical dimension to explore for efficiency and scalability, as deep learning models grow significantly larger and more complex. After all, the biological ...
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