journal article·2025Open access

A Generative Model-Based Network Framework for Ecological Data Reconstruction

Shuqiao Liu, Hongyan Zhou, Xuebo Chen, Zhao Zhang

Computers, Materials & Continua· Volume 82· Issue 1

Abstract

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection systems. Combining Strengths, Weaknesses, Opportunities, Threat... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Scientific Computing and Data Management · Advanced Database Systems and Queries · Semantic Web and Ontologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (38)

Show source-provided references
1. MODIS green-tide detection with a squeeze and excitation oriented generative adversarial network10.1109/ACCESS.2022.3180331 ↗
2. Bridging modalities: A survey of cross-modal image-text retrieval10.62762/CJIF.2024.361895 ↗
3. A cyber-physical system based on On-Board Diagnosis (OBD-II) for smart city10.62762/TIS.2024.329126 ↗
4. GAN-based LUCC prediction via the combination of prior city planning information and land-use probability
5. Transfer learning-based rich feature analysis on leather images for species prediction
6. Hyperspectral remote sensing reflectamce data augmentation method for red tide dominant species based on condition generative adversarial net
7. Multi-attention Generative Adversarial Network for multi-step vegetation indices forecasting using multivariate time series10.1016/j.engappai.2023.107563 ↗
8. Classification and detection of insects from field images using deep learning for smart pest management: A systematic review10.1016/j.ecoinf.2021.101460 ↗
9. Automated marine oil spill detection algorithm based on single-image generative adversarial network and YOLO-v8 under small samples10.1016/j.marpolbul.2024.116475 ↗
10. Semi-recurrent CNN-based VAE-GAN for sequential data generation
11. Spatiotemporal pattern of mangrove forests in bulacan using satellite data fusion method and machine learning
12. Adversarial examples for generative models
13. Monitoring data augmentation of spectral information using VAE and GAN for soft-failure identification
14. A comprehensive review of synthetic data generation in smart farming by using variational autoencoder and generative adversarial network10.1016/j.engappai.2024.107881 ↗
15. M. Arjovsky, S. Chintala, and L. Bottou, “Wasserstein GAN,” 2017, arXiv:1701.07875v3.
16. Unsupervised representation learning with deep convolutional generative adversarial networks
17. Modelling air quality in street canyons: A review10.1016/S1352-2310(02)00857-9 ↗
18. Ecosystem mapping in mountainous areas by fusing multi-source data and the related knowledge
19. Data fusion for connectivity analysis between ocean regions
20. ESR-GAN: Environmental signal reconstruction learning with generative adversarial network10.1109/JIOT.2020.3018621 ↗
21. Design of dynamic monitoring system of lake ecosystem based on geographical information system
22. Distributed decision fusion for large scale IoT-ecosystem
23. Implementing sustainable ecotourism in Lafour region, Iran: Applying a clustering method based on SWOT analysis10.1016/j.jclepro.2021.129716 ↗
24. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS10.1016/S0377-2217(03)00020-1 ↗
25. An extension of TOPSIS for group decision making10.1016/j.mcm.2006.03.023 ↗
26. Ecological risk assessment and transmission of soil heavy metals in pastoral areas of the Tibetan plateau based on network environment analysis10.1016/j.scitotenv.2023.167197 ↗
27. Analysis of the ecological tourism development model based on SWOT
28. Fully convolutional networks for semantic segmentation10.1109/TPAMI.2016.2572683 ↗
29. T. Xu et al., “AttnGAN: Fine-grained text to image generation with attentional generative adversarial networks,” 2017, arXiv:1711.10485v1.10.1109/CVPR.2018.00143 ↗
30. N. Ruiz et al., “DreamBooth: Fine tuning text-to-image diffusion models for subject-driven generation,” 2023, arXiv:2208.12242v2.10.1109/CVPR52729.2023.02155 ↗
31. Conditional generative adversarial nets
32. Zero-VAE-GAN: Generating unseen features for generalized and transductive zero-shot learning
33. D. P. Kingma and M. Welling, “Auto-encoding variational bayes,” 2013, arXiv:1312.6114v3.
34. Generative adversarial nets
35. MIWAE: Deep generative modelling and imputation of incomplete data sets
36. Quantitative SWOT analysis: A structured and collaborative approach to reintroduction site selection for the endangered Pacific pocket mouse10.1016/j.jnc.2022.126268 ↗
37. M. Abadi et al., “TensorFlow: Large-scale machine learning on heterogeneous distributed systems,” 2016, arXiv:1603.04467v2.
38. TensorLayer: A versatile library for efficient deep learning development