A5051531132- Context-Aware Activity Recognition Systems
- Atmospheric aerosols and clouds
- Quantum Computing Algorithms and Architecture
- Neural Networks and Reservoir Computing
- Machine Learning in Healthcare
- Water Quality and Pollution Assessment
- Identification and Quantification in Food
- Remote Sensing and Land Use
- Artificial Intelligence in Healthcare
- Metabolomics and Mass Spectrometry Studies
- Inertial Sensor and Navigation
- Meteorological Phenomena and Simulations
- Human Mobility and Location-Based Analysis
- Recommender Systems and Techniques
- Quantum Information and Cryptography
- Medical Image Segmentation Techniques
- Robotics and Sensor-Based Localization
- Vehicle License Plate Recognition
- Tea Polyphenols and Effects
- Brain Tumor Detection and Classification
- Remote-Sensing Image Classification
- Climate variability and models
- Traditional Chinese Medicine Studies
- Space Satellite Systems and Control
- AI in cancer detection
Tongji University
2024
Queen's University Belfast
2024
Institute of Atmospheric Physics
2024
Chinese Academy of Sciences
2006-2024
University of Chinese Academy of Sciences
2024
State Key Laboratory of Remote Sensing Science
2006
Next Point-of-Interest (POI) recommendation task focuses on predicting the immediate next position a user would visit, thus providing appealing location advice. In light of this, graph neural networks (GNNs) based models have recently been emerging as breakthroughs for this due to their ability learn global preferences and alleviate cold-start challenges. Nevertheless, most existing methods merely focus relations between POIs, neglecting higher-order information including trajectories...
Diabetes is a chronic disorder causing millions of people to suffer from severe complications such as heart attacks, kidney failures, and permanent vision loss. This study aims find an optimal choice among the five selected models that perform best on diabetes prediction, thus provide valuable insights in early detection diabetes. compares predictive performance machine learning Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM). The preprocessed Pima Indians (PID)...
Abstract In this study, a method for assimilating FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances (CER) is investigated, and the impact of on water vapor analysis rainstorm forecasting examined through observing system simulation experiments actual case experiments. The high proportion inverted humidity profiles in pixels main reason negative effect assimilation mid‐to‐lower troposphere. To address this, relevant constraint conditions are incorporated into cost...
Abstract Efficient quantum compiling is essential for complex algorithms realization. The Solovay–Kitaev (S–K) theorem offers a theoretical lower bound on the required operations approaching any unitary operator. However, it still an open question that this can be actually reached in practice. Here, we present efficient compiler which, first time, approaches S–K practical implementations, both single-qubit and two-qubit scenarios, marking significant milestone. Our leverages deep...
In recent years, encoder-decoder networks have focused on expanding receptive fields and incorporating multi-scale context to capture global features for objects of varying sizes. However, as deepen, they often discard fine spatial details, impairing precise object localization. Additionally, conventional decoders' use interpolation upsampling leads a loss context, diminishing edge segmentation accuracy. To address the above problems, we propose novel parallel multi-resolution network,...