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NumtaDB - Assembled Bengali Handwritten Digits

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arxiv 1806.02452 v1 pith:AWHYTCXV submitted 2018-06-06 cs.CV

Samiul Alam , Tahsin Reasat , Rashed Mohammad Doha , Ahmed Imtiaz Humayun This is my paper · ORCID
classification cs.CV
keywords bengalidatasetassembleddigitsnumtadbalgorithmsalongavailable
verification ladder T0 review T1 audit T2 compute T3 formal
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To benchmark Bengali digit recognition algorithms, a large publicly available dataset is required which is free from biases originating from geographical location, gender, and age. With this aim in mind, NumtaDB, a dataset consisting of more than 85,000 images of hand-written Bengali digits, has been assembled. This paper documents the collection and curation process of numerals along with the salient statistics of the dataset.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. WeightCLIP: Aligning Datasets and Models for Weight Space Learning

    cs.LG 2026-07 conditional novelty 6.0 of 10

    Contrastive dataset–weight alignment reshapes weight-space latents so dataset prompts retrieve, generate, and refine neural nets better than prior weight-space methods.

  2. HishabNet: Detection, Localization and Calculation of Handwritten Bengali Mathematical Expressions

    cs.CV 2019-09 conditional novelty 5.0 of 10

    A YOLOv3-based system detects Bengali digits and operators and evaluates handwritten arithmetic expressions, reporting 98.6% mAP on a new self-made dataset.

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