Bin Li

ORCID: 0000-0003-4826-4737
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About
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Research Areas
  • Granular flow and fluidized beds
  • Advanced Vision and Imaging
  • Mineral Processing and Grinding
  • Fluid Dynamics and Heat Transfer
  • Lattice Boltzmann Simulation Studies
  • Robotics and Sensor-Based Localization
  • Heat and Mass Transfer in Porous Media
  • Fluid Dynamics and Mixing
  • Satellite Image Processing and Photogrammetry
  • Hydraulic Fracturing and Reservoir Analysis
  • Enhanced Oil Recovery Techniques
  • Particle Dynamics in Fluid Flows
  • Computer Graphics and Visualization Techniques
  • Nuclear Materials and Properties
  • Advanced Image and Video Retrieval Techniques

Key Laboratory of Nuclear Radiation and Nuclear Energy Technology
2021-2024

Tsinghua University
2021-2024

The solid-flow pattern of free drainage is important to the design a silo and prediction discharge rate granular systems, flow in monolayer pebble bed formed two-dimensional (2D) reveals rules three-dimensional (3D) silo. whole-field PTV platform here contains with adjustable configurations (MPBAC) corresponding programs for particle recognition, amending, matching. Using this platform, all particles beds are traced whole process drainage. average mass residence time distribution (RTD)...

10.1021/acs.iecr.2c01926 article EN Industrial & Engineering Chemistry Research 2022-09-12

Scale-aware monocular depth estimation poses a significant challenge in computer-aided endoscopic navigation. However, existing methods that do not consider the geometric priors struggle to learn absolute scale from training with sequences. Additionally, conventional face difficulties accurately estimating details on tissue and instruments boundaries. In this paper, we tackle these problems by proposing novel enhanced scale-aware framework only uses images modeling for estimation....

10.48550/arxiv.2408.07266 preprint EN arXiv (Cornell University) 2024-08-13
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