Image Technology Investigation Based on Fingerprint Devices and Artificial Intelligence

In response to the inaccurate visual positioning of fingerprint data images in investigative techniques, a new method based on wireless networks and artificial intelligence is proposed. The new method integrates wireless networks and image vision, while enhancing fingerprint data and images using cross temporal generative networks and channel state information. The research results indicated that the maximum positioning error value of the new model was 1.3m, which was 0.7m, 0.2m, and 0.4m lower than other models. The minimum positioning error value in indoor environments was 0.9m, which was lower compared with the 1.0m, 1.4m, and 1.6m of other models. The model used in the study had higher localization performance and recognition accuracy. The average accuracy was improved by about 4.5% compared with the TDF method with the lowest accuracy. The average root mean square error value was relatively low, with a minimum of 2.15. Compared with the highest SDF model, it was 4.43 lower. Therefore, the proposed method has better fingerprint recognition localization and investigation techniques, which has a better research guidance role for fingerprint localization and image recognition localization.

@article{Zhao2024,
  title     = {Image Technology Investigation Based on Fingerprint Devices and Artificial Intelligence},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {6},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Xuemei Zhao},
  doi       = {10.14569/IJACSA.2024.0150641},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150641}
}