Machine Learning

Conveyor belts are the most widespread means of transportation for large quantities of materials in the mining sector. This dataset contains 388 images of structures with and without dirt buildup.

One can use this dataset for experimentation on classifying the dirt buildup.

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This is the image of data.

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Supplementary materials of the paper titled 

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We obtained 6 million instances to be used as an analysis for modelling CO2 behavior. The Data Logging and sensors nodes acquisition are every 1 second.

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Pedestrian detection has never been an easy task for computer vision and automotive industry. Systems like the advanced driver assistance system (ADAS) highly rely on far infrared (FIR) data captured to detect pedestrians at nighttime. The recent development of deep learning-based detectors has proven the excellent results of pedestrian detection in perfect weather conditions. However, it is still unknown what is the performance in adverse weather conditions.

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This dataset covers cellular communication signals in the SCF format. There is a total of 60000 signal instances, 36000 of them are reserved as training data and the rest is for the test. The SNR levels are between 1 dB and 15 dB.

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4953 Views

Endoscopy is a widely used clinical procedure for the early detection of cancers in hollow-organs such as oesophagus, stomach, and colon. Computer-assisted methods for accurate and temporally consistent localisation and segmentation of diseased region-of-interests enable precise quantification and mapping of lesions from clinical endoscopy videos which is critical for monitoring and surgical planning. Innovations have the potential to improve current medical practices and refine healthcare systems worldwide.

Last Updated On: 
Sat, 02/27/2021 - 05:11

The data set includes three sub-data sets, namely the DAGM2007 data set, the ground crack data set, and the Yibao bottle cap defect data set, which are divided into a training set and a test set, in which the positive and negative samples are unbalanced.

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Computer vision can be used for environment-adaptive control of robotic exoskeletons and prostheses. However, small-scale and private training datasets have impeded the development of image classification algorithms (e.g., convolutional neural networks) to recognize the walking environment. To address these limitations, we developed ExoNet, a large-scale dataset of wearable camera images (i.e., egocentric perception) of real-world walking environments.

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A Chinese dataset for table-to-text generation named WIKIBIOCN which inculeds 33,244 biography sentences with related tables from Chinese Wikipedia (July 2018).

The dataset is divided into training set (30,000), verification set (1000) and test set (2,244).

 

 

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