A5087598861- Advancements in Battery Materials
- Handwritten Text Recognition Techniques
- Supercapacitor Materials and Fabrication
- Graphene research and applications
- Advanced Battery Materials and Technologies
- Advanced Image and Video Retrieval Techniques
- Nanomaterials for catalytic reactions
- Vehicle License Plate Recognition
- Multimodal Machine Learning Applications
- Crystal Structures and Properties
- Image Processing and 3D Reconstruction
- Catalytic Processes in Materials Science
- Image Retrieval and Classification Techniques
- MXene and MAX Phase Materials
- Perovskite Materials and Applications
- Boron and Carbon Nanomaterials Research
- Mathematics, Computing, and Information Processing
- Advanced battery technologies research
- Semiconductor materials and interfaces
- Covalent Organic Framework Applications
- Metal-Organic Frameworks: Synthesis and Applications
- Advanced Battery Technologies Research
- ATP Synthase and ATPases Research
- Coenzyme Q10 studies and effects
- Electrocatalysts for Energy Conversion
Changzhou University
2021-2024
Nanjing Tech University
2011-2022
Southwest University
2019-2021
Pennsylvania State University
2016-2020
Beijing Graphene Institute
2016-2017
Laboratoire de Mécanique des Sols, Structures et Matériaux
2013
Chengdu University of Technology
2009
Oklahoma State University
1994
We present a robust end-to-end neural-based model to attentively recognize text in natural images. Particularly, we focus on accurately identifying irregular (perspectively distorted or curved) text, which has not been well addressed the previous literature. Previous research reading often works with regular (horizontal and frontal) does adequately generalize processing perspective distortion curving effects. Our work proposes overcome this difficulty by introducing two learning components:...
Page segmentation and table detection play an important role in understanding the structure of documents. We present a page algorithm that incorporates state-of-the-art deep learning methods for segmenting three types document elements: text blocks, tables, figures. propose multi-scale, multi-task fully convolutional neural network (FCN) tasks semantic element contour detection. The accurately predicts probability at each pixel classes. instance level "edges" around occurrence. conditional...
Scene text detection has attracted great attention these years. Text potentially exist in a wide variety of images or videos and play an important role understanding the scene. In this paper, we present novel algorithm which is composed two cascaded steps: (1) multi-scale fully convolutional neural network (FCN) proposed to extract block regions, (2) instance (word line) aware segmentation designed further remove false positives obtain word instances. The can accurately localize line...
We describe a facile and eco‐friendly solution approach to chemically reduce graphene oxide (GO) high‐quality using nontoxic inexpensive reductants. The reduction process mechanism of group reductants were systematically studied. These perform quite differently in terms rate ( l ‐ascorbic acid [ ‐AA] > d ‐fructose sucrose glucose sodium sulfite), density small sp 2 domains ‐AA sulfite ‐fructose), degree sucrose), stability the reduced GO suspension sulfite). shows highest reducing...
Recently, silicon-based anode materials have garnered significant attention from researchers due to their high theoretical specific capacity. However, these are highly prone volume expansion, which significantly hinders its...
We describe a novel strategy for fabrication of unique minky-dot-fabric-shaped composite well-organized porous TiO2 microspheres and reduced-graphene-oxide (rGO) sheets used as an anode material in lithium-ion batteries. In this composite, the act hosts fast efficient lithium storage while rGO serve highly conductive substrates. Such structural features assure large contact area between electrolyte electrode, favorable diffusion electrons Li+ ions. Moreover, they can accommodate volume...
A unique hierarchically nanostructured composite of iron oxide/carbon (Fe3O4/C) nanospheres-doped three-dimensional (3D) graphene aerogel has been fabricated by a one-pot hydrothermal strategy. In this novel aerogel, uniform Fe3O4 nanocrystals (5-10 nm) are individually embedded in carbon nanospheres (ca. 50 forming pomegranate-like structure. The matrix suppresses the aggregation nanocrystals, avoids direct exposure encapsulated to electrolyte, and buffers volume expansion. Meanwhile,...
High-capacity anode materials of transition-metal oxides (TMOs) usually undergo low conductivities and drastic volume variation derived from a multielectron-transfer conversion reaction mechanism, which seriously hinder the cycling stability rate performance toward their commercialization. Herein, free-standing Fe2O3/C shells/reduced graphene oxide (Fe2O3/C/RGO) film as an additive-free is fabricated by facile two-step strategy accompanied physical cross-linking feature chitosan. In this...
Catalysts with an open hollow structure can enhance the mass transfer capability of catalyst during reaction process, thereby further improving catalytic performance. In this work, uniform and monodisperse flying-squircher-shaped Al-MOFs were synthesized via a solvothermal method. Furthermore, Al2O3-supported metallic Ni (termed Ni–Al2O3–HFA) was Kirkendall effect for hydrogenation–alkylation cascade by employing as-synthesized as carrier impregnation Ni(NO3)2·6H2O through calcination...
Abstract A series of novel hierarchical nanoporous microstructures have been synthesized through one-step chemical reduction micron size Cu 2 O and Co 3 4 particles. By controlling the time, non-porous microcubes sequentially transform to Cu/Cu O/Cu dented cubic composites hollow eightling-like microparticles. The mechanism involved in complex structural evolution is explained based on oxygen diffusion Kirkendall effect. exhibit superior electrochemical performance as compared solid...