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Found 6 papers, 6 papers with code
BN-DRISHTI: Bangla Document Recognition through Instance-level Segmentation of Handwritten Text Images
Handwriting recognition remains challenging for some of the most spoken languages, like Bangla, due to the complexity of line and word segmentation brought by the curvilinear nature of writing and lack of quality datasets.
Ranked #1 on
Handwritten Word Segmentation
on BanglaWriting
Handwritten Line Segmentation
Handwritten Text Recognition
+4
BN-HTRd: A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation
Our line segmentation approach takes care of the variability involved in different writing styles, accurately segmenting complex handwritten text lines of curvilinear nature.
Ranked #2 on
Handwritten Line Segmentation
on BN-HTRd
Handwritten Line Segmentation
Handwritten Text Recognition
+2
N-gram Statistical Stemmer for Bangla Corpus
Our proposed system has enhanced the aforementioned exploration by actualizing one of the stemming algorithms called N-gram stemming.
Extracting RDF Triples from Raw Text
This manuscript manifests the results of our work on extracting RDF triples from raw text data.
Comparison of Classical Machine Learning Approaches on Bangla Textual Emotion Analysis
Detecting emotions from text is an extension of simple sentiment polarity detection.
Topic Classification from Text Using Decision Tree, K-NN and Multinomial Naïve Bayes
One of the central motivations behind Natural Language Processing is detecting patterns.
Ranked #1 on
Topic Classification
on Amazon Product Data
