AISSLab Breast Cancer Dataset: Toward General AI Harmonization with Real Mammogram Imaging
The AISSLab Breast Cancer Dataset is a collection of mammogram images by experts from the Ma'amon's Diagnostic Centre Mammogram Images for Breast Cancer (MDCMI-BC) in Yemen. It is designed to support advancements in breast cancer research and computer-aided diagnosis (CAD) systems. To facilitate research in breast cancer detection, focusing on harmonizing AI with diverse imaging data. This dataset emphasizes improving diagnostic accuracy and is available for academic and clinical research applications.
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Public Roads Visual Pollution Dataset
Visual Pollution (VP) is the visible deterioration and bad aesthetic quality of the natural and human-made landscapes. It also refers to the disruptive occurrence that limits the movability of the people on the public roads such as excavation barriers, potholes, and dilapidated sidewalks. The real VP dataset is collected from the kingdom of Saudi Arabia (KSA) regions via the Ministry of Municipal and Rural Affairs and Housing (MOMRAH) and used to develop the proposed deep learning framework.
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Arabic Handwritten Legal Amount (AHLA) Dataset
The AHLA dataset is collected by distributing an advanced designed report with Arabic native speakers. Our dataset contains two kinds of Arabic handwritten:
- Arabic word-level images that express legal amounts of bank cheques, including the colloquial words used in writing Arabic numbers.
- Arabic legal amount sentence images.
The primary objective of compiling this comprehensive dataset is to furnish a diverse range of Arabic language samples. These samples are intended for training and testing systems capable of autonomously recognizing and comprehending handwritten legal amounts on financial documents. Subsequently, the aim is to convert these semantic expressions into their respective numeric currency totals, facilitating digital processing and banking operations.
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