Minglin Chen

ORCID: 0000-0003-4681-706X
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About
Contact & Profiles
Research Areas
  • Electrocatalysts for Energy Conversion
  • Coastal and Marine Dynamics
  • 3D Shape Modeling and Analysis
  • Computer Graphics and Visualization Techniques
  • Fluid Dynamics Simulations and Interactions
  • Wave and Wind Energy Systems
  • 3D Surveying and Cultural Heritage
  • Nanomaterials for catalytic reactions
  • Glioma Diagnosis and Treatment
  • Fuel Cells and Related Materials
  • Catalytic Processes in Materials Science
  • Advanced Vision and Imaging
  • Pituitary Gland Disorders and Treatments
  • Electrochemical Analysis and Applications
  • Advanced battery technologies research
  • Advanced Neural Network Applications
  • Forensic Anthropology and Bioarchaeology Studies
  • Catalysis and Hydrodesulfurization Studies
  • Metal-Organic Frameworks: Synthesis and Applications
  • Robot Manipulation and Learning
  • Earthquake and Tsunami Effects
  • Radiomics and Machine Learning in Medical Imaging
  • Gait Recognition and Analysis
  • Autonomous Vehicle Technology and Safety
  • Geotechnical Engineering and Underground Structures

Chongqing Jiaotong University
2022-2025

Sun Yat-sen University
2020-2025

Lanzhou Petrochemical Polytechnic
2021-2023

Merchants Chongqing Communications Research and Design Institute
2023

Shenzhen Institutes of Advanced Technology
2020

Beijing University of Chemical Technology
2017-2019

Shenzhen Bao'an District People's Hospital
2019

Xiamen University
2019

Recently, unsupervised domain adaptation in satellite pose estimation has gained increasing attention, aiming at alleviating the annotation cost for training deep models. To this end, we propose a self-training framework based on domain-agnostic <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">geometrical constraints</i> . Specifically, train neural network to predict 2D keypoints of and then use PnP estimate pose. The poses target samples are...

10.1109/taes.2023.3250385 article EN cc-by IEEE Transactions on Aerospace and Electronic Systems 2023-03-01

This paper proposes a dual-stream 3D space-time convolutional neural network action recognition framework. The original depth map sequence data is set as the input in order to study global characteristics of each category. high correlation within human itself considered time domain, and then deep motion introduced another stream network. Furthermore, corresponding skeleton third whole Although has advantage including information, it also confronted with problems existence rate change,...

10.3390/app9040716 article EN cc-by Applied Sciences 2019-02-19

3D scene generation conditioned on text prompts has significantly progressed due to the development of 2D diffusion models. However, textual description scenes is inherently inaccurate and lacks fine-grained control during training, leading implausible generation. As an intuitive feasible solution, layout allows for precise specification object locations within scene. To this end, we present a text-to-scene method (namely, Layout2Scene) using additional semantic as prompt inject positions....

10.48550/arxiv.2501.02519 preprint EN arXiv (Cornell University) 2025-01-05

Semantic instance completion aims to recover the complete 3D shapes of foreground objects together with their labels from a partial 2.5D scan scene. Previous works have relied on full supervision, which requires ground-truth annotations, in form bounding boxes and objects. This has greatly limited real-world application because acquisition data is very costly time-consuming. To address this bottleneck, we propose Weakly-Supervised Instance Completion Network (WSSIC-Net), learns point cloud...

10.1109/tip.2024.3520013 article EN IEEE Transactions on Image Processing 2025-01-01

At present, box-girder superstructures are commonly used in coastal bridges, and their hydrodynamic performance under extreme waves such as tsunamis has attracted a lot of attention. There is lack research focusing on the effect lateral restraining stiffness wave condition. In this paper, two-dimensional numerical model based RANS equation SST k-ω turbulence established. Combined with dynamic mesh updating technique, superstructure characteristics movable solitary were investigated. To...

10.3390/jmse10081019 article EN cc-by Journal of Marine Science and Engineering 2022-07-26

Novel view synthesis aims at rendering any posed images from sparse observations of the scene. Recently, neural radiance fields (NeRF) have demonstrated their effectiveness in synthesizing novel views a bounded However, most existing methods cannot be directly extended to 360° unbounded scenes where camera orientations and scene depths are unconstrained with large variations. In this paper, we present spherical field (SRF) for efficient scenes. Specifically, represent 3D as multiple...

10.1109/tip.2024.3409052 article EN IEEE Transactions on Image Processing 2024-01-01

Abstract A novel composite Fe‐bpdc‐C 3 N 4 ‐CA catalyst (where bpdc stands for 2,2′‐bipyridine‐3,3′‐dicarboxylic acid and CA carbon aerogel) with a high nitrogen content was synthesized through the in situ encapsulation of nitrogen‐containing metal organic frameworks along g‐C into porous CAs. The characteristics catalysts calcined at different temperatures were determined by means TEM, XRD, Raman spectroscopy, XPS, BET measurements. results demonstrate successful doping heteroatoms...

10.1002/celc.201800479 article EN ChemElectroChem 2018-05-02

Metal–organic framework (MOF) materials can be used as precursors to prepare non-precious metal catalysts (NPMCs) for oxygen reduction reaction (ORR). Herein, we prepared a novel MOF material (denoted Co-bpdc) and then combined it with multi-walled carbon nanotubes (MWCNTs) form Co-bpdc/MWCNTs composites. After calcination, the cobalt ions from Co-bpdc were converted into Co nanoparticles, which distributed in graphite layers MWCNTs Co-bpdc/MWCNTs. The characterized by TEM (Transmission...

10.3390/catal7120364 article EN Catalysts 2017-11-27

Background: It is often difficult to diagnose pituitary microadenoma (PM) by MRI alone, due its relatively small size, variable anatomical structure, complex clinical symptoms, and signs among individuals. We develop validate a deep learning -based system PM from MRI. Methods: A total of 11,935 infertility participants were initially recruited for this project. After applying the exclusion criteria, 1,520 (556 patients 964 controls subjects) included further stratified into 3 non-overlapping...

10.3389/fmed.2021.758690 article EN cc-by Frontiers in Medicine 2021-11-29

Abstract One major limitation for polymer electrolyte membrane fuel cells is the sluggish cathode kinetics. Development of efficient noble‐free catalysts key resolution to problem oxygen reduction reaction (ORR) in both acid and alkaline solutions. Herein, we report a new type non‐precious‐metal catalyst ORR through direct pyrolysis poly[2,2′‐(1,1′‐cobaltocenium)‐5,5′‐dibenzimidazole]. The cobalt oxides were produced after at 900 °C (Cp 2 ‐Co + ‐PBI‐900, where PBI polybenzimidazole)....

10.1002/celc.201600762 article EN ChemElectroChem 2017-02-28

Ultrafine PdCo bimetallic nanoclusters with Co atom-modified Pd active sites were highly dispersed and confined in an m-NC material for selective semi-hydrogenation of alkynes to alkenes.

10.1039/d2dt02765h article EN Dalton Transactions 2022-01-01

Selective hydrogenation of alkynes to obtain alkenes is a key reaction in petrochemical and fine chemical industries. However, the development stable highly selective catalysts with uniformly dispersed active sites still immensely challenging for semi-hydrogenation alkynes. In this study, N-doped porous carbon nanospheres (NPCNs) were synthesized by nanoemulsion self-assembly subsequently carbonization method. Ultrafine PdCu bimetallic nanoparticles (NPs) immobilized on NPCNs. The obtained...

10.1039/d2cp04845k article EN Physical Chemistry Chemical Physics 2022-12-21
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