Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...

Agent memory remains a problem that enterprises want to fix, as agents forget some instructions or conversations the longer they run. Anthropic believes it has solved this issue for its Claude Agent ...

When I first started working with multi-agent collaboration (MAC) systems, they felt like something out of science fiction. It’s a group of autonomous digital entities that negotiate, share context, ...

I have read the paper and it seemed to be a single-label multi-classification problem. But the code use BCE and sigmoid instead of crossEntropy and softmax. So does it mean that the patient may have ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

Introduction: Accurate environmental image classification is essential for ecological monitoring, climate analysis, disaster detection, and sustainable resource management. However, traditional ...

Abstract: Multi-label classification (MLC) involves assigning multiple labels to each instance from a predefined set of labels. With the increasing prevalence of multi-label datasets in real-world ...

X says it is creating a new profile label to signify accounts that are parodies of a person or entity. The company says it “designed these labels to increase transparency and to ensure that users are ...