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 ...
Graph Neural Networks (GNNs) have emerged as the leading approach for graph learning tasks across various domains, including recommender systems, social networks, and bioinformatics. However, GNNs ...
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 ...
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 ...
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 ...
The Moxi area in the Sichuan Basin is dominated by carbonate gas reservoirs, where gas productivity is most strongly influenced by their pore types. Fractured caves are the most favorable pore ...
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