Abstract
New study results on artificial intelligence have been published. According to news originating from Xinxiang, People's Republic of China, by NewsRx correspondents, research stated, “Image aesthetics processing (IAP) is used primarily to enhance the aesthetic quality of images.” Funders for this research include National Natural Science Foundation of China; Science And Technology Research Project of Henan Province. Our news correspondents obtained a quote from the research from Henan Normal University: “However, IAP faces several issues, including its failure to analyze the influence of visual scene information and the difficulty of deploying IAP capabilities to mobile devices. This study proposes an automatic IAP system (IAPS) for mobile devices that integrates machine learning and traditional image-processing methods. First, we employ an extremely computation-efficient deep learning model, ShuffleNet, designed for mobile devices as our scene recognition model. Then, to enable computational inferencing on resource-constrained edge devices, we use a modern mobile machine-learning library, TensorFlow Lite, to convert the model type to TFLite format. Subsequently, we adjust the image contrast and color saturation using group filtering, respectively. These methods enable us to achieve maximal aesthetic enhancement of images with minimal parameter adjustments.”
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