Chaohong Tan
Biographic Data
| ID | 7922242 |
|---|---|
| NAME | Chaohong Tan |
| GIVEN NAMES | Chaohong |
| FAMILY NAME | Tan |
| SIGNATURE | TAN C |
| AFFILIATIONS | Beijing University of Civil Engineering and Architecture |
| ORCID | 0000-0003-3337-3447 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
SGG-Mvar
Cross-modal retrieval is crucial for achieving accurate and efficient information retrieval by establishing semantic correlations between heterogeneous images and text. However, traditional image-text training sets suffer from information asymmetry, which includes short lengths and limited sentence structures. This phenomenon often results in insufficient representations of essential visual information. We introduce RichDataset, which offers exte…
Occurrence and Health Risks of Heavy Metals in Drinking Water of Self-Supplied Wells in Northern China
Self-supplied wells, an important water resource in remote and scattered regions, are commonly deteriorated by environmental pollution and human activity. In this study, 156 self-supplied well-water samples were collected from remote and scattered areas of Inner Mongolia (NMG), Heilongjiang (HLJ), and the suburbs of Beijing (BJ) in Northern China. Twenty-four heavy metals were identified by using the inductively coupled plasma-mass spectrometry (…
No prominent works on this page.
Occurrence and Health Risks of Heavy Metals in Drinking Water of Self-Supplied Wells in Northern China
Self-supplied wells, an important water resource in remote and scattered regions, are commonly deteriorated by environmental pollution and human activity. In this study, 156 self-supplied well-water samples were collected from remote and scattered areas of Inner Mongolia (NMG), Heilongjiang (HLJ), and the suburbs of Beijing (BJ) in Northern China. Twenty-four heavy metals were identified by using the inductively coupled plasma-mass spectrometry (…
SGG-Mvar
Cross-modal retrieval is crucial for achieving accurate and efficient information retrieval by establishing semantic correlations between heterogeneous images and text. However, traditional image-text training sets suffer from information asymmetry, which includes short lengths and limited sentence structures. This phenomenon often results in insufficient representations of essential visual information. We introduce RichDataset, which offers exte…
Advanced Image and Video Retrieval Techniques (1 work) · Artificial Intelligence (1 work) · Chemistry (1 work) · Computer Science (1 work) · Computer vision (1 work) · Environmental Chemistry (1 work) · Environmental health (1 work) · Environmental Science (1 work) · Graph (1 work) · Heavy Metal Exposure and Toxicity (1 work)