Finding Concepts with Unexpected Multi-Label Objects Based on Shared Subspace Method

We refer to these properties as safety trigger conditions since, when such a condition is detected (i.e., the system has entered a warning state), the aim is to trigger

The main advantage of the proposed approach over other multi-label techniques is the production of a p-value for each possible labelset of a new unseen instance, which can be

According to the user to select an image to generate positive sample packs and anti-packages, using multi-instance learning algorithms to learn, using the image retrieval

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

n: number of participants; SD, standard deviation; BP: blood pressure; CVD: cardiovascular disease; multimorbidity: 2 or more self- reported chronic diseases;

The best known transformation method is the binary relevance (BR) approach [21]. This approach trans- forms a multi-label classification problem with Q possible classes into

Basically, in the first case, for each frame, the objects are detected and then associated (using a data association algo- rithm) to the previously tracked objects that are the

In a phase of writer identification, using Kernel Orthogonal Mutual Subspace Method (KOMSM), subspace was calculated by the eigen vectors.. The result obtained through