Handwritten Digit Recognition
22 papers with code • 1 benchmarks • 5 datasets
MNIST
NumtaDB
MNIST-MIX
DigiLeTs
Latest papers
Advancing Multilingual Handwritten Numeral Recognition with Attention-driven Transfer Learning
CVLab-SHUT/HandWrittenDigitRecognition
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IEEEXplore 2024
In this work, we present a robust and cost-effective approach that handles multilingual handwritten numeral recognition across a wide range of languages.
PolyLUT: Learning Piecewise Polynomials for Ultra-Low Latency FPGA LUT-based Inference
We show that by using polynomial building blocks, we can achieve the same accuracy using considerably fewer layers of soft logic than by using linear functions, leading to significant latency and area improvements.
Features extraction and reduction techniques with optimized SVM for Persian/Arabic handwritten digits recognition
Recognizing handwritten digits is one of the most active research areas in computer vision, as there are a variety of applications, such as automatic identification of digits in bank checks and vehicle numbers.
Learning the Precise Feature for Cluster Assignment
gyh5421/unified_deep_clustering
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Based on this, we propose a general-purpose deep clustering framework which radically integrates representation learning and clustering into a single pipeline for the first time.
Bangla Handwritten Digit Recognition and Generation
Handwritten digit or numeral recognition is one of the classical issues in the area of pattern recognition and has seen tremendous advancement because of the recent wide availability of computing resources.
Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation
GabrieleLagani/SpikingGrid
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Previous work has shown that it is possible to train neuronal cultures on Multi-Electrode Arrays (MEAs), to recognize very simple patterns.
VSQL: Variational Shadow Quantum Learning for Classification
Classification of quantum data is essential for quantum machine learning and near-term quantum technologies.
A Comparative Analysis on Bangla Handwritten Digit Recognition with Data Augmentation and Non-Augmentation Process
To improve the performance of the Bangla handwritten digit recognition system, we have designed a model, in which all basic Bangla digits have been classified.
Effective Handwritten Digit Recognition using Deep Convolution Neural Network
This paper proposed a simple neural network approach towards handwritten digit recognition using convolution.
MNIST-MIX: A Multi-language Handwritten Digit Recognition Dataset
In this letter, we contribute a multi-language handwritten digit recognition dataset named MNIST-MIX, which is the largest dataset of the same type in terms of both languages and data samples.
