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A fast monocular 6D pose estimation method for textureless objects based on perceptual hashing and template matching.
Front Robot AI
January 2025
Department of Materials and Production, Aalborg University, Aalborg, Denmark.
Object pose estimation is essential for computer vision applications such as quality inspection, robotic bin picking, and warehouse logistics. However, this task often requires expensive equipment such as 3D cameras or Lidar sensors, as well as significant computational resources. Many state-of-the-art methods for 6D pose estimation depend on deep neural networks, which are computationally demanding and require GPUs for real-time performance.
View Article and Find Full Text PDFHigh performance liquid chromatography (HPLC) is a key analytical technique that is used in a number of fields. Improving the separation efficiency, stability, and universality of HPLC has been a continuing analytical-chemistry focus. In chromatographic separation, factors such as the composition and ratio of the mobile phase, the type of stationary phase, and the dimensions of the chromatographic column significantly affect the separation efficiency.
View Article and Find Full Text PDFMorphological Characteristics of Inferior Pole Patellar Fractures and a Finite-Element Analysis Combined With a Retrospective Clinical Study of Anchor Suture and Titanium Cable Cerclage Treatment.
Orthop Surg
January 2025
Department of Orthopedics Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China.
Objective: Inferior pole patellar fractures (IPPFs) pose a significant challenge due to their complex fracture patterns and high risk of complications associated with current treatment methods. This study aims to (1) characterize the fracture patterns of IPPFs using fracture mapping and (2) compare the biomechanical stability and clinical outcomes of treatment with anchor suture with patellar cerclage versus Kirschner-wire tension band combined with patellar cerclage.
Methods: (1) A retrospective analysis was conducted on 61 patients with IPPF.
Neuromorphic computing is a brain-inspired approach to hardware and algorithm design that efficiently realizes artificial neural networks. Neuromorphic designers apply the principles of biointelligence discovered by neuroscientists to design efficient computational systems, often for applications with size, weight and power constraints. With this research field at a critical juncture, it is crucial to chart the course for the development of future large-scale neuromorphic systems.
View Article and Find Full Text PDFRandom resistive memory-based deep extreme point learning machine for unified visual processing.
Nat Commun
January 2025
Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics, Chinese Academy of Sciences, 100029, Beijing, China.
Visual sensors, including 3D light detection and ranging, neuromorphic dynamic vision sensor, and conventional frame cameras, are increasingly integrated into edge-side intelligent machines. However, their data are heterogeneous, causing complexity in system development. Moreover, conventional digital hardware is constrained by von Neumann bottleneck and the physical limit of transistor scaling.
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