Yancun Yang

ORCID: 0000-0003-0785-6007
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About
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Research Areas
  • Advanced Chemical Sensor Technologies
  • Spectroscopy and Chemometric Analyses
  • Evolutionary Game Theory and Cooperation
  • Evolution and Genetic Dynamics
  • Mathematical and Theoretical Epidemiology and Ecology Models
  • Nutritional Studies and Diet
  • Advanced Measurement and Detection Methods
  • Vehicle emissions and performance
  • Advanced Algorithms and Applications
  • Smart Agriculture and AI
  • Air Quality Monitoring and Forecasting
  • Water Quality Monitoring Technologies
  • Neural Networks and Applications
  • Air Quality and Health Impacts
  • Remote Sensing and Land Use
  • Image Retrieval and Classification Techniques

Ludong University
2013-2024

Food-image recognition plays a pivotal role in intelligent nutrition management, and lightweight methods based on deep learning are crucial for enabling mobile deployment. This capability empowers individuals to effectively manage their daily diet using devices such as smartphones. In this study, we propose an Efficient Hybrid Food Recognition Net (EHFR–Net), novel neural network that integrates Convolutional Neural Networks (CNN) Vision Transformer (ViT). We find the context of food-image...

10.3390/nu16020200 article EN Nutrients 2024-01-08

Consumer behaviors and habits in food choices impact their physical health have implications for climate change global warming. Efficient image recognition can assist individuals making more environmentally friendly healthier dietary using end devices, such as smartphones. Simultaneously, it enhance the efficiency of server-side training, thereby reducing carbon emissions. We propose a lightweight deep neural network named Global Shuffle Net (GSNet) that efficiently recognize images. In...

10.1109/tafe.2024.3386713 article EN IEEE Transactions on AgriFood Electronics 2024-05-02

Recently, considerable research efforts have been devoted to food recognition for its great potential applications in human health. Much work so far has focused on directly extracted deep visual features via Convolutional Neural Networks, which require significant computational resources and training time. The high requirements hardware severely limit the application of mobile devices sustainable extension server side. Therefore, how design an efficient high-performance lightweight neural...

10.1002/int.23050 article EN International Journal of Intelligent Systems 2022-09-02

Food image recognition has recently been given considerable attention in the multimedia field light of its possible implications on health. The characteristics dispersed distribution ingredients food images put forward higher requirements long-range information extraction ability neural networks, leading to more complex and deeper models. Nevertheless, lightweight version is essential for improved implementation end devices sustained server-side expansion. To address this issue, we present...

10.1145/3680285 article EN ACM Transactions on Multimedia Computing Communications and Applications 2024-07-22

Traditionally, individual intensities to perform games are always assumed be fixed in networks (e.g. depend on the number of their neighbors). However, increase own fitness or payoffs, individuals may adjust reaction external environment changes real scenarios. With this motivation, we have studied adjustment by considering average payoff neighbors network a spatial prisoner’s dilemma game. An will unilaterally (decrease) its intensity between itself and when is greater than equal (lower...

10.1142/s0129183118500705 article EN International Journal of Modern Physics C 2018-07-04

A new troubleshooting algorithm for solving assignment problem based on existing algorithms is proposed, and an analysis the related theory given. By applying to Lagrange relaxation of multi-dimensional data association multi-passive-sensor multi-target location systems, comparing simulation results with that Hungarian which classical optimal algorithm, multi-layer order-searching a sub-optimal performance conditions are summarized. Theory prove effectiveness superiority algorithm.

10.1109/jsee.2013.00021 article EN Journal of Systems Engineering and Electronics 2013-02-01
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