A5000853324- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
- Remote-Sensing Image Classification
- Visual Attention and Saliency Detection
- Image Retrieval and Classification Techniques
- Embedded Systems and FPGA Design
- Image Enhancement Techniques
- High Entropy Alloys Studies
- High-Temperature Coating Behaviors
- Advanced Neural Network Applications
- Neural Networks Stability and Synchronization
- Video Analysis and Summarization
- Advanced Algorithms and Applications
- Simulation and Modeling Applications
- Advanced Computing and Algorithms
- Glass properties and applications
- Shape Memory Alloy Transformations
- Image Processing Techniques and Applications
- Advanced Image Processing Techniques
- Multimodal Machine Learning Applications
- Machine Learning and ELM
- Infrared Target Detection Methodologies
- Human Pose and Action Recognition
- X-ray Diffraction in Crystallography
- Ferroelectric and Piezoelectric Materials
North China University of Science and Technology
2012-2024
University of Chinese Academy of Sciences
2024
Institute of High Energy Physics
2022-2024
Chinese Academy of Sciences
2022-2024
Institute of Information Engineering
2019
Beijing Jiaotong University
2012-2015
TED University
2012-2014
Tianjin University
2006-2012
Tangshan College
2011
ABSTRACT Solid solutions are ubiquitous in metals and alloys. Local chemical ordering (LCO) is a fundamental sub-nano/nanoscale process that occurs many solid can be used as microstructure to optimize strength ductility. However, the formation of LCO has not been fully elucidated, let alone how provide efficient routes for designing achieve synergistic effects on both superb Herein, we propose control negative enthalpy With engineering solutions, genetic components formed refractory...
Zeolitic imidazolate framework (ZIF) glasses featuring nanoscale porosity have attracted significant attention due to their potential applications in catalysis, energy storage, gas sorption, and separation. However, mechanical properties may limit some of these applications. In this work, we investigate the structural origins variation zinc-based ZIF-62 (ZnIm2–xbImx) with different benzimidazolate (bIm) (Im) ratios. This is achieved using large-scale molecular dynamics simulations a recent...
Semi-supervised sparse feature selection, which can exploit the small number labeled data and large unlabeled simultaneously, has become an important technique in many applications on large-scale web image owing to its high efficiency effectiveness. Recently, graph Laplacian-based semi-supervised selection obtained considerable attention, but it suffers with only few because Laplacian regularization is short of extrapolating power. In this paper we propose a novel framework based Hessian...
Facing a large number of unlabeled data and small labeled data, semisupervised sparse feature selection has received increasing attention in recent years. However, most algorithms are developed for single-view cannot naturally handle multiview data. Moreover, existing methods based on Laplacian regularization, which is lack extrapolating power. To overcome the above-mentioned drawbacks, we present Hessian semi-supervised (MHSFS) framework this paper. MHSFS can directly accomplish by...
The supervised model based on deep learning has made great achievements in the field of image classification after training with a large number labeled samples. However, there are many categories without or only few samples practice, and some even have no at all. proposed zero-shot greatly reduces dependence for models. Nevertheless, limitations similarity visual features semantic predefined fixed metric (e.g., as Euclidean distance), well problem gap mapping process. To address these...
Web image annotation has become a critical research issue in recent years. It is beneficial to develop effective semisupervised feature selection methods exploit the labeled data and unlabeled simultaneously for web annotation. However, graph Laplacian based semi-supervised learning suffer from fact that sparse coordinates are biased toward constant embedding often cannot preserve local topology well as we expected. In this paper propose novel method on second-order Hessian energy, namely...