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Retrieval from Noisy E-Discovery Corpus in the Absence of Training Data., , and . SIGIR, page 755-758. ACM, (2015)An Efficient Feature Vector for Segmentation-Free Recognition of Online Cursive Handwriting Based on a Hybrid Deep Neural Network., , and . DAS, page 435-440. IEEE Computer Society, (2018)Simplet and its Application in Signal Encryption., and . Multidimens. Syst. Signal Process., 15 (4): 375-394 (2004)Clustered Semi-Supervised Relevance Feedback., and . CIKM, page 1723-1726. ACM, (2015)Offline handwritten Devanagari word recognition: Information fusion at feature and classifier levels., , and . ACPR, page 720-724. IEEE, (2015)A Hybrid Model for End to End Online Handwriting Recognition., , , and . ICDAR, page 658-663. IEEE, (2017)Does Deeper Network Lead to Better Accuracy: A Case Study on Handwritten Devanagari Characters., , , , and . DAS, page 411-416. IEEE Computer Society, (2018)Bangla Handwritten Character Segmentation Using Structural Features: A Supervised and Bootstrapping Approach., , , and . ACM Trans. Asian Low Resour. Lang. Inf. Process., 15 (4): 29:1-29:26 (2016)Indian Statistical Institute Kolkata at PR-SOCO 2016: A Simple Linear Regression Based Approach., and . FIRE (Working Notes), volume 1737 of CEUR Workshop Proceedings, page 48-51. CEUR-WS.org, (2016)