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Researchers from the Harbin Institute of Technology in China have developed a new framework called DL-CEndo to improve the efficiency of data transmission in wireless capsule endoscopy. The framework uses deep learning to compress unnecessary data and send low-resolution luma images, conserving energy in the device. Additionally, a colorization model is implemented to reconstruct the colors of unnecessary images, and a demo for fast and smart summarization is introduced to aid physicians in the review process. The DL-CEndo framework achieved a high compression ratio of 93.20% and ensures fast diagnostics for physicians. [Extracted from the article]