Please use this identifier to cite or link to this item:
http://111.93.178.142:25000/jspui/handle/123456789/2701| Title: | Handwritten character recognition system |
| Authors: | Chowdhury, Harshdip |
| Keywords: | Handwritten Character Recognition (HCR) System, hybrid deep teaming model combining Convolutional Neural Networks (CNNs) for spatial feature extraction with Recurrent Neural Networks (RNNs} Transformer-based OCR model, TrOCR MN/ST, KaggleA-Z, and 1AM Handwriting Database were used, representing a diverse range of writing styles |
| Issue Date: | 2025 |
| Publisher: | Brainware University |
| URI: | http://111.93.178.142:25000/jspui/handle/123456789/2701 |
| Appears in Collections: | Dept. of CSE-CS & DS |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Abstract_CSE_PR_13.pdf | Handwritten character recognition system | 787.96 kB | Adobe PDF | View/Open |
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