A5058316544- Advanced Fiber Optic Sensors
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Mass Spectrometry Techniques and Applications
- Natural Language Processing Techniques
- Chemical Synthesis and Analysis
- Advanced Chemical Sensor Technologies
- Nuclear Physics and Applications
- Handwritten Text Recognition Techniques
- Particle physics theoretical and experimental studies
- Machine Learning in Materials Science
- Video Analysis and Summarization
- Biomedical Text Mining and Ontologies
Automatic font generation remains a challenging research issue, primarily due to the vast number of Chinese characters, each with unique and intricate structures. Our investigation previous studies reveals inherent bias capable causing structural changes in characters. Specifically, when generating character similar to, but different from, those training samples, is prone either correcting or ignoring these subtle variations. To address this concern, we propose novel Skeleton Font Generation...
The primary objective of Optical Chemical Structure Recognition is to identify chemical structure images into corresponding markup sequences. However, the complex two-dimensional structures molecules, particularly those with rings and multiple branches, present significant challenges for current end-to-end methods learn one-dimensional directly. To overcome this limitation, we propose a novel Ring-Free Language (RFL), which utilizes divide-and-conquer strategy describe in hierarchical form....
The Super $τ$-Charm facility (STCF) is an electron-positron collider proposed by the Chinese particle physics community. It designed to operate in a center-of-mass energy range from 2 7 GeV with peak luminosity of $0.5\times 10^{35}{\rm cm}^{-2}{\rm s}^{-1}$ or higher. STCF will produce data sample about factor 100 larger than that present factory -- BEPCII, providing unique platform for exploring asymmetry matter-antimatter (charge-parity violation), in-depth studies internal structure...
The primary objective of Optical Chemical Structure Recognition is to identify chemical structure images into corresponding markup sequences. However, the complex two-dimensional structures molecules, particularly those with rings and multiple branches, present significant challenges for current end-to-end methods learn one-dimensional directly. To overcome this limitation, we propose a novel Ring-Free Language (RFL), which utilizes divide-and-conquer strategy describe in hierarchical form....