Image Processing
The problem of effective disposal of the trash generated by people has rightfully attracted major interest from various sections of society in recent times. Recently, deep learning solutions have been proposed to design automated mechanisms to segregate waste. However, most datasets used for this purpose are not adequate. In this paper, we introduce a new dataset, TrashBox, containing 17,785 images across seven different classes, including medical and e-waste classes which are not included in any other existing dataset.
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Guava fruit production is one of the main sources of economic growth in Asian countries, the world production of guava in 2019 was 55 million tons. Guava disease is an important factor in economic loss as well as quantity and quality of guava. The original guava fruit disease dataset consist of 38 images of phytophthora, 30 images of root and 34 images of scab guava disease with 650x650x3 pixel.
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The dataset images are composed of varying degrees of hypertensive retinopathy. In the compressed file my_experiment_Resnet50, there are ten subfolders corresponding to the training data of ten models.
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The integration of communication and artificial intelligence has become a development trend, one of the applications is semantic communication, but the current research lacks the support of comprehensive datasets. To solve this problem, we built a new image and video dataset, named SCO dataset, for the researches on semantic communication and computing. First, we introduce the peculiarities of the dataset, which contains 5100 images and 138 video clips. Secondly, we we give the data generation and processing methods of the dataset, including images and videos.
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Sign languages are the most common mode of communication with and between hearing-impaired individuals. In the Arab world, Arabic sign language is used with different dialects supporting a distinct set of rules for the gestures used. With research on natural language processing advancing, models have been developed to translate sign language to spoken language and vice versa. However, Arabic sign language has rarely been studied due to the lack of availability of datasets dealing with Arabic sign language.
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<p>Images from Sentinel 2 for dehazing. Contains 3 folders, one with original images, one with dehazed images at default exponent of 0.8 and the last with failed images with fine tuned exponent (thus becoming successful).</p>
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This cherry tree disease detection dataset is a multimodal, multi-angle dataset which was constructed for monitoring the growth of cherry trees, including stress analysis and prediction. An orchard of cherry trees is considered in the area of Western Macedonia, where 577 cherry trees were recorded in a full crop season starting from Jul. 2021 to Jul. 2022. The dataset includes a) aerial / Unmanned Aerial Vehicle (UAV) images, b) ground RGB images/photos, and c) ground multispectral images/photos.
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