Published October 17, 2018 | Version 1.0
Dataset Open

NFFA-EUROPE - 100% SEM Dataset - Old

Description

This dataset should not be used, because a huge amount of replicas has been found. Please use the new version. Dataset of 25,430 SEM images produced at CNR-IOM (Trieste, Italy). Images are classified into 10 categories in a folder structure. Classification labels have been checked by a group of nanoscientists on the web site http://sem-classifier.nffa.eu and only those images which have been validated by the 100% of the group have been included in the dataset. The dataset is appropriate for the purposes of this study and in general for visual object recognition software research. Any scientific metadata associated to the measure is not present in the images. The dataset is therefore relevant as a whole, being the single images entirely detached from any specific information or scientific detail related to the displayed subject. This work has been done within the NFFA-EUROPE project (www.nffa.eu) and has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 654360 NFFA-Europe.

Files

Files (10.7 GB)

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704.8 MB Download
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PID: http://hdl.handle.net/11304/32d477d3-3e59-44c5-af8f-6f73bd43ce8a
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PID: http://hdl.handle.net/11304/c800075a-8f0b-4017-955c-461bd7feae76
197.9 MB Download
Checksum: md5:98a988b167ff25528b80ab8bf7585c04

PID: http://hdl.handle.net/11304/54ac9625-7524-4d42-910d-883e3d7c7e00
3.3 GB Download
Checksum: md5:005ffe16579c6352d3d521f58de56e8d

PID: http://hdl.handle.net/11304/9cb46071-d4fb-4136-82ec-e63f189ed307
2.2 GB Download
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PID: http://hdl.handle.net/11304/c8c15d67-023f-4ad1-acad-ac82e483fc3e
2.5 GB Download
Checksum: md5:851e6daf0e7ce45b68dbe9eb1338807e

PID: http://hdl.handle.net/11304/5e941610-4031-4622-94c8-b90441046e68
119.7 MB Download
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866.7 MB Download
Checksum: md5:0a85315213af1c32a14555d46e8f093a

PID: http://hdl.handle.net/11304/627a30cb-308f-4f46-82ab-075a444ef313
709.0 MB Download

Additional details

Identifiers

b2rec
655995db63b7425f894eb08b6f67f46b
b2rec
ec3355627ec64d6887492aae16b9dd4d