A5047189393- Anomaly Detection Techniques and Applications
- Speech and Audio Processing
- Traffic Prediction and Management Techniques
- Mobile Agent-Based Network Management
- Ultra-Wideband Communications Technology
- Indoor and Outdoor Localization Technologies
- Respiratory viral infections research
- Semantic Web and Ontologies
- Video Surveillance and Tracking Methods
- Bluetooth and Wireless Communication Technologies
- Subtitles and Audiovisual Media
- Media Influence and Health
- Network Packet Processing and Optimization
- IoT and Edge/Fog Computing
- Cyclone Separators and Fluid Dynamics
- Cloud Computing and Resource Management
- Traffic control and management
- Internet of Things and Social Network Interactions
- Mental Health via Writing
- Industrial Gas Emission Control
- Music and Audio Processing
- Oil, Gas, and Environmental Issues
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- COVID-19 diagnosis using AI
Shanghai Maritime University
2024
University of Augsburg
2022-2024
Zhejiang University of Finance and Economics
2023
University of Electronic Science and Technology of China
2021
Tongji University
2013
Xi'an Polytechnic University
2011
Since the COronaVIrus Disease 2019 (COVID-19) outbreak, developing a digital diagnostic tool to detect COVID-19 from respiratory sounds with computer audition has become an essential topic due its advantages of being swift, low-cost, and eco-friendly. However, prior studies mainly focused on small-scale datasets. To build robust model, large-scale multi-sound FluSense dataset is utilised help cough in this study. Due gap between COVID-19-related datasets consisting only, transfer learning...
Translating mental health recognition from clinical research into real-world application requires extensive data, yet existing emotion datasets are impoverished in terms of daily monitoring, especially when aiming for self-reported anxiety and depression recognition. We introduce the Japanese Daily Speech Dataset (JDSD), a large in-the-wild speech dataset consisting 20,827 samples 342 speakers 54 hours total duration. The data is annotated on Depression Anxiety Mood Scale (DAMS) – 9 emotions...
Affective computing (AC), like most other areas of computational research, has benefited tremendously from advances in deep learning (DL). These have opened up new horizons AC research and practice. Yet, as DL dominates the community’s attention, there is a danger overlooking emerging trends artificial intelligence (AI) research. Furthermore, over-reliance on one particular technology may lead to stagnating progress. In an attempt foster exploration complementary directions, we provide...
Monitoring urban flow timely and accurately is crucial for many industrial applications – from planning to traffic control in the smart cities. This work introduces a new method inferring fine-grained with internet of mobile things such as taxis bikes. We tackle problem perspective present novel deep learning UrbanODE (Urban inference Neural Ordinary Differential Equations). Furthermore, provides flexible balance between accuracy computational efficiency, which important computation...
Learning English as a foreign language requires an extensiveuse of cognitive capacity, memory, and motor skills in order to orallyexpress one’s thoughts clear manner. Current speech recognition in-telligence focuses on recognising learners’ oral proficiency from fluency,prosody, pronunciation, grammar’s perspectives. However, the ca-pacity clearly naturally expressing idea is high level cognitivebehaviour which can hardly be represented by these detailed segmen-tal dimensions, indeed do not...
Nowadays, microblog has emerged as the most promising social networking service in Web2.0 age with diverse features for information dissemination, interpersonal communication and many other aspects. Chinese shows great potential owing to rich marketing source powerful media influence brought by huge user population. As community is largely influenced some authoritative users, identifying these users understanding dissemination pattern are theoretically practically significant us promote...
Detecting COVID-19 from audio signals, such as breathing and coughing, can be used a fast efficient pre-testing method to reduce the virus transmission. Due promising results of deep learning networks in modelling time sequences, we present temporal-oriented broadcasting residual that achieves computation high accuracy with small model size. Based on EfficientNet architecture, our novel network, named Temporaloriented ResNet (TorNet), constitutes block. The network obtains useful...