Artificial Intelligence

The data set is from the Case Western Reserve University Rolling Bearing data set. SK6205 bearing located at the drive end is selected as the research object, and the acquisition frequency is 12KHz. The fault type is divided into three types, namely inner ring fault, rolling body fault and outer ring fault, and each fault type is divided into three fault sizes: 0.007, 0.014 and 0.021 inches.The length of each sample is 1024 and the repetition rate is 50%

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We collected fundus photos from the Kangnam Sacred Heart Hospital, Hallym University School of Medicine, Seoul, South Korea (IRB approval number: 2022-10-026), that were obtained from 2000 to September 2022. The fundus photographs were taken by five skilled examiners using the KOWA Nonmyd 8S Fundus Camera (KOWA company, Japan). Among the 2,000 images, we chose 50 test images that were characterized as ``bad-quality'' due to one of the following reasons: media opacity, small pupil, or poor patient cooperation.

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This dataset consists of 462 field of views of Giemsa(dye)-stained and field(dye)-stained thin blood smear images acquired using an iPhone 10 mobile phone with a 12MP camera. The phone was attached to an Olympus microscope with 1000× objective lens. Half of the acquired images are red blood cells with a normal morphology and the other half have a Rouleaux formation morphology.

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This dataset comprises 1718 annotated images extracted from 29 video clips recorded during Endoscopic Third Ventriculostomy (ETV) procedures, each captured at a frame rate of 25 FPS. Out of these images, 1645 are allocated for the training set, while the remainder is designated for the testing set. The images contain a total of 4013 anatomical or intracranial structures, annotated with bounding boxes and class names for each structure. Additionally, there are at least three language descriptions of varying technicality levels provided for each structure.

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To develop radio frequency-based drone recognition, we release an RF spectrogram dataset, named DroneRFb-Spectra. All signals of drones were collected by a Universal Software Radio Peripheral (USRP) device, recording three Industrial Scientific Medical (ISM) bands under urban scenarios. The classes cover 7 common brands, i.e., DJI, Vbar, FrSky, Futaba, Taranis, RadioLink, and Skydroid, with a total number of 14460. Each spectrogram has been downsampled to the size of 512x512 from the original IQ data with a length of 50ms by using the short-time Fourier transform.

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This is the first multi-view, semi-indoor gait dataset captured with the DAVIS346 event camera. The dataset comprises 6,150 sequences, capturing 41 subjects from five different view angles under two lighting conditions. Specifically, for each lighting condition and view angle, there are six sequences representing normal walking (NM), three sequences representing walking with a backpack (BG), three sequences representing walking with a portable bag (PT), and three sequences representing walking while wearing a coat (CL).

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¢This study delves into the connections between green ELT, DEIB, virtual reality, mediation, life skills, and task-based teaching, learning, and assessment in the context of sustainable and inclusive education. The study emphasizes the significance of incorporating ecological concepts into language instruction, advocating for diversity, fairness, and inclusivity in learning environments, and using virtual reality technology to augment language acquisition.

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Human facial data hold tremendous potential to address a variety of classification problems, including face recognition, age estimation, gender identification, emotion analysis, and race classification. However, recent privacy regulations, such as the EU General Data Protection Regulation, have restricted the ways in which human images may be collected and used for research.

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This is a dataset about minimizing maritime passenger transfer in ship routing. Consists of data on the distance between ports, the number of passengers from the port of origin to the port of destination, ships speed, and the duration of berthing at ports.

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This archive includes three popular traffic datasets: Abilene, GEANT, and TaxiBJ. 

Abilene and GEANT is network traffic datsets and TaxiBJ is urban traffic datset.

 

This archive includes three popular traffic datasets: Abilene, GEANT, and TaxiBJ. 

Abilene and GEANT is network traffic datsets and TaxiBJ is urban traffic datset.

 

This archive includes three popular traffic datasets: Abilene, GEANT, and TaxiBJ. 

Abilene and GEANT is network traffic datsets and TaxiBJ is urban traffic datset.

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