Incorporating the image formation process into deep learning appears to improve network performance. Various studies have applied this concept to different fields, including fluorescence imaging, skin cancer classification, and image restoration. The approach has also been explored in other areas, such as precision agriculture and medical imaging, although its connection to these fields is not entirely clear from the available information.