Vol. 1 No. 12 (2024)

Issue 12 of IJETAA features an innovative research article advancing the field of computational imaging through deep learning applications. The study, authored by Ziran Wei, Jianlin Zhang, Wei Du, and Zhiruo Wang, introduces a breakthrough in real-time single-pixel imaging technology. Through the integration of deep convolutional neural networks and novel four-channel parallel processing methods, the research achieves real-time video capture at 256×256 resolution with 33 frames per second, addressing a longstanding challenge in the field. The researchers demonstrate significant improvements in both image quality and processing speed compared to traditional compressed sensing approaches. The work presents a comprehensive solution for real-time high-resolution imaging, with potential applications across medical imaging, surveillance systems, and other advanced imaging applications. This research exemplifies the journal's commitment to publishing transformative technological advances that bridge theoretical frameworks with practical implementations.