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The Lemon Leaf Disease Dataset (LLDD) is a high-quality image dataset designed for training and evaluating machine learning models for lemon leaf disease classification. The dataset contains 9  classes of images of healthy and diseased lemon leaves, such as; Anthracnose. Bacterial Blight, Citrus Canker, Curl Virus, Deficiency Leaf, Dry Leaf, Healthy Leaf, Sooty Mould, Spider Mites, making it suitable for tasks such as plant disease instance segmentation, detection, image classification, and deep learning applications in agriculture.

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Following the setup of previous works [8, 16], we conducted experiments on various bit image restoration tasks.

We utilized a dataset of 2000 16-bit images, with training

data sourced from SINTEL [37] and FIVE-K [38]. SINTEL

is an animated short film dataset containing over 20,000 16-

bit lossless images with a resolution of 436 × 1024 pixels. In

FIVE-K, randomly select images from 5,000 16-bit natural

images for the experiment.The test set includes 8 images

randomly chosen from the SINTEL dataset (referred to as

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