Embedded Files
Papers:
Papers:
Amir Soleimani, Christof Monz, Marcel Worring. "Non-factoid Long Question Answering", EACL (accepted), 2021
I Sekuli ́c, A Soleimani, M Aliannejadi, F Crestani. ”Longformer for MS MARCO DocumentRe-ranking Task”, arXiv, 2020
Amir Soleimani, Christof Monz, Marcel Worring. "BERT for Evidence Retrieval and Claim Verification", European Conference on Information Retrieval (ECIR), 2020
Amir Soleimani, Nasser M. Nasrabadi, Elias Griffith, Jason Ralph, Simon Maskell, "Convolutional Neural Networks for Aerial Vehicle Detection and Recognition", IEEE National Aerospace and Electronics Conference (NAECON), 2018
Amir Soleimani, Nasser M. Nasrabadi, "Convolutional Neural Networks for Aerial Multi-Label Pedestrian Detection", 21st International Conference on Information Fusion (FUSION), 2018
Amir Soleimani, Babak N Araabi, Kazim Fouladi, "Deep Multitask Metric Learning for Offline Signature Verification", Pattern Recognition Letters, 2016
Amir Soleimani, Kazim Fouladi, Babak N Araabi, "UTSig: A Persian Offline Signature Dataset", IET Biometrics, 2016 (dataset: mlcm.ut.ac.ir/Datasets.html)
Amir Soleimani, Kazim Fouladi, Babak N Araabi,"Persian Offline Signature Verification based on Curvature and Gradient Histograms", 6th International Conference on Computer and Knowledge Engineering (ICCKE), 2016
NLQuAD is a non-factoid long question answering dataset from BBC news articles. NLQuAD’s question types and the long length of its context documents as well as answers, make it a challenging real-world task. NLQuAD consists of news articles as context documents, interrogative sub-headings in the articles as questions, and body paragraphs corresponding to the sub-headings as contiguous answers to the questions. NLQuAD contains 31k non-factoid questions and long answers collected from 13k BBC news articles.
Check github for the dataset and codes
Dataset: UTSig (University of Tehran Offline Signature Dataset)
Dataset: UTSig (University of Tehran Offline Signature Dataset)
UTSig has 115 classes containing: 27 genuine signatures; 3 opposite-hand signed samples and 42 simple forgeries. Each class belongs to one specific authentic person. UTSig totally has 8280 images collected from undergraduate and graduate students of University of Tehran and Sharif University of Technology. Signatures were scanned with 600 dpi resolution and stored as 8-bit Tiff files.
From here you can see some samples (5 complete classes). Moreover you can see UTSig preview version (one small size sample per class).
New! Cropped, One-Folder, and PNG Version (Suggested!) [UTSig_Crop]
In this new version, signatures were cropped and all samples were located in one folder with format of CxxxGxx or CxxxFxx (C=Class, G=Genuine, F=Forgery)
Download the Small Version of Persian offline signature dataset [UTSig 60 MB]
Full-Size Version of University of Tehran Signature Dataset [Full-size UTSig 249 MB]
Please note that, any work made public should be referred to the UTSig Paper in IET Biometrics journal.
For any question or reporting problems in dataset or downloading process please contact A.Soleimani.B {at} gmail.com
Page updated
Google Sites
Report abuse