Intelligent News Image Formatter: AI‑Based Cropping and Selection System for News List Images
This article introduces the Intelligent News Formatter, an AI‑driven system that tackles news‑app list‑image problems by using face detection, object detection, deep‑learning based cropping, image quality filtering, and similarity removal to automatically produce aesthetically pleasing and information‑rich thumbnails.
Business Background – News‑app list images heavily influence user experience, yet they often suffer from cropping errors and poor selection, leading to incomplete faces or low‑information thumbnails.
Image Cropping – The solution combines face detection (HOG, DeepFace) and object detection (Faster R‑CNN, YOLO, SSD) to locate important regions such as faces, bodies, and objects, ensuring these areas are retained during automatic cropping.
Image Selection – Low‑quality images are filtered using image‑classification models (AlexNet, VGG16, ResNet50), while similar images are detected via hashing (aHash, dHash, pHash) and deep‑learning feature vectors, removing redundant or overly similar thumbnails.
Conclusion – The deployed system achieves satisfactory online cropping results, though challenges remain with special cases like cartoons; ongoing model updates and expanded training data are planned to improve quality filtering and similarity detection.
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