Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...

Abstract: 3D object detectors based on LiDAR have been extensively used in autonomous and robotic systems. Efficient voxel-based models must downsample their feature space to reduce computation, which ...

Abstract: Currently, due to the different distribution of data for each user, many personalized federated learning (PFL) methods have emerged to meet the personalized needs of different users. However ...

Abstract: We propose a multipoint-to-point all-optical channel aggregation scheme using Talbotbased processing and power-division multiplexing, enhancing scalability of uplink traffic in a coherent ...

Abstract: Ensuring precise segmentation of point clouds is essential for intelligent inspection in transmission line corridors. The massive scale, unordered distribution, and complex structures of ...

Abstract: As the integration of renewable energy sources (RES) such as wind and solar power into the power grid increases, the primary challenge lies in the high integration costs and the complexity ...

SINGAPORE, SINGAPORE, SINGAPORE, March 1, 2026 /EINPresswire.com/ — As the generative AI market hurtles toward a projected $1 trillion valuation by the end of 2026 ...

Abstract: Change Point Detection (CPD) aims to identify moments of abrupt distribution shifts in data streams. Real-world high-dimensional CPD remains challenging due to data pattern complexity and ...

Abstract: In this paper, a Backward Attentive Fusing Network with Local Aggregation Classifier (BAF-LAC) is proposed to improve the performance of 3D point cloud semantic segmentation. It consists of ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...