Artificial Intelligence
This is a dataset on normal and early stage (stage I and II) endometrial cancer, comprising a total of 300 MRI images of patients (100 normal, 100 stage I and II), 207 patients (77 healthy, 100 stage IA (50 stage IA, 50 stage IB), and 30 stage II patients. From January 1, 2018 to December 31, 2020, he underwent 1.5-T MRI in Fujian Maternal and Child Health Hospital, with an average age of 55.7 years. Patient age The images in this dataset were all provided by the Radiology Department of Fujian Provincial Maternal and Child Health Care Hospital and may contain privacy concerns.
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366 Views
The Nematode Detection Dataset is a comprehensive collection of 1,368 high-quality microscope images specifically curated for the advancement of agricultural pest management through machine learning. This dataset has been meticulously assembled to aid in the detection, identification, and analysis of four key types of nematodes that are critical to global agriculture: Meloidogyne (Root-knot nematodes), Globodera pallida (Potato cyst nematodes), Pratylenchus (Root-lesion nematodes), and Ditylenchus (Stem nematodes).
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24 Views
These datasets are gathered from an array of four gas sensors to be used for the odor detection and recognition system. The smell inspector Kit IX-16 used to create the dataset. each of 4 sensor has 16 channels of readings. Odors of different 12 samples are taken from these six sensors
1- Natural Air
2- Fresh Onion
3- Fresh Garlic
4- Black Lemon
5- Tomato
6- Petrol
7- Gasoline
8- Coffee
9- Orange
10- Colonia Perfume
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396 Views
These datasets are gathered from an array of six gas sensors to be used for the odor recognition system. The sensors those used to create the data set are; Df-NH3, MQ-136, MQ-135, MQ-8, MQ-4, and MQ-2.
odors of different 10 samples are taken from these six sensors
1- Natural Air
2- Fresh Onion
3- Fresh Garlic
4- Fresh Lemon
5- Tomato
6- Petrol
7- Gasoline
8- Coffee 1,2
9- Orange
10- Colonia Perfume
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573 Views
DataSet used in learning process of the traditional technique's operation, considering different devices and scenarios, perform the commutation through Pure ALOHA protocol, and make the device to operate with the best possible configuration.The control of energy consumption is essential for the operation of battery-operated systems, such as those used in IoT networks and sensors. The algorithms commonly employed for this purpose involve optimization functions with considerable complexity and rigorous control of the test environment.
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352 Views
This is a test dataset for comparison with the latest multi-objective evolutionary algorithms. We have split the experiment into two groups in high and low dimensions respectively, and the experimental results are outstanding. We used IGD as the performance metric, and the data in parentheses are the std of 20 independent repetitions of the experiment and were analyzed for significance.
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67 Views
This is a part of the Cityintrusion-Multicategory dataset for testing and training the network. This dataset contains 2502 training images and 429 validation images. Because our task is a joint task of segmentation and detection. Therefore, we provide the two different sub-dataset for segmentation and detection, respectively. In the seg folder, we provide the original images for training and validation. Besides, the corresponding labels also are provided. Training and validation have 2502 and 429, respectively.
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198 Views
This is a part of the Cityintrusion-Multicategory dataset for testing and training the network. This dataset contains 2502 training images and 429 validation images. Because our task is a joint task of segmentation and detection. Therefore, we provide the two different sub-dataset for segmentation and detection, respectively. In the seg folder, we provide the original images for training and validation. Besides, the corresponding labels also are provided. Training and validation have 2502 and 429, respectively.
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54 Views
This is a part of the Cityintrusion-Multicategory dataset for testing and training the network. This dataset contains 2502 training images and 429 validation images. Because our task is a joint task of segmentation and detection. Therefore, we provide the two different sub-dataset for segmentation and detection, respectively. In the seg folder, we provide the original images for training and validation. Besides, the corresponding labels also are provided. Training and validation have 2502 and 429, respectively.
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4 Views
This is a part of the COVID-CTset dataset for testing and training the network. This dataset contains 12058 CT slices. It was gathered from Negin medical center that is located at Sari in Iran. This medical center uses a SOMATOM Scope model and syngo CT VC30-easyIQ software version for capturing and visualizing the lung HRCT radiology images from the patients. The format of the exported radiology images was 16-bit grayscale DICOM format with 512*512 pixels resolution.
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123 Views