Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data ...

The thesis not only showcases technical advancements but also underscores the importance of interpretability and scalability in agricultural AI solutions. Farmers and stakeholders are more likely to ...

Overview Clear prompts help machine learning models become more accurate and reliable.Role-specific prompts generate focused and practical technical answers.Det ...

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...

A system that generates images by inducing random fluctuations in a laser beam could slash energy use compared with standard ...

Over the past decades, computer scientists have developed many computational tools that can analyze and interpret images.

We implement the neuromorphic radar system through a printed-circuit board (PCB) prototype and carry out simulations for the IC version. Our experiments verify NeuroRadar’s ability to empower resource ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Demographic bias gaps are closing in face recognition, but how training images are sourced is becoming the field’s biggest privacy fight.