Handwritten Digit Recognition
23 papers with code • 1 benchmarks • 5 datasets
MNIST
NumtaDB
MNIST-MIX
DigiLeTs
Most implemented papers
Frank-Wolfe Network: An Interpretable Deep Structure for Non-Sparse Coding
We propose an interpretable deep structure namely Frank-Wolfe Network (F-W Net), whose architecture is inspired by unrolling and truncating the Frank-Wolfe algorithm for solving an $L_p$-norm constrained problem with $p\geq 1$.
BDNet: Bengali Handwritten Numeral Digit Recognition based on Densely connected Convolutional Neural Networks
Sufianlab/BDNet
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BDNet is a densely connected deep convolutional neural network model used to classify (recognize) Bengali handwritten numeral digits.
Lightweight and Unobtrusive Data Obfuscation at IoT Edge for Remote Inference
ntu-aiot/ObfNet
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Executing deep neural networks for inference on the server-class or cloud backend based on data generated at the edge of Internet of Things is desirable due primarily to the limited compute power of edge devices and the need to protect the confidentiality of the inference neural networks.
Effective Handwritten Digit Recognition using Deep Convolution Neural Network
This paper proposed a simple neural network approach towards handwritten digit recognition using convolution.
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.
VSQL: Variational Shadow Quantum Learning for Classification
Classification of quantum data is essential for quantum machine learning and near-term quantum technologies.
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.
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.
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.
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.
