Infrared optoelectronic functional materials are essential for applications in lasers, photodetectors, and infrared imaging, ...

In today’s digital transformation era, software testing is undergoing a pivotal evolution. Ajay Seelamneni, a researcher and innovator in automated testing, delves into the transformative capabilities ...

Because we believe the goal of a deep learning framework is to convert computation into useful intelligence, we have made performance a core pillar of Burn. We strive to achieve top efficiency by ...

Zhang is part of a research team that has developed a deep learning model to detect mental health symptoms and risk factors ...

🦉 OWL is a cutting-edge framework for multi-agent collaboration that pushes the boundaries of task automation, built on top of the CAMEL-AI Framework. Our vision is to revolutionize how AI agents ...

In a recent advance, a multi-disciplinary team of researchers developed a machine learning framework that adapts to changes in the geometry of the physical settings of PDEs. Called DIMON, the new ...

Estimating the pose of hand-held objects is a critical and challenging problem in robotics and computer vision. While ...

Researchers from UCLA and Meta AI have introduced d1, a novel framework using reinforcement learning (RL) to significantly enhance the reasoning capabilities of diffusion-based large language models ...

Researchers pioneered the integration of CNN-LSTM with bond stress-slip constitutive modeling and proposed a deep ...

By employing multimodal data fusion, merging traffic volumes, weather patterns, and vehicle telemetry, the system boosts the contextual accuracy of forecasts and decision-making. The deep ...

Abstract: This paper investigates the deep learning based approaches for simultaneous wireless information and power transfer (SWIPT). The quality-of-service (QoS) constrained sumrate maximization ...