On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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5 results for “writer-independent”

Writer Independent Offline Signature Recognition Using Ensemble Learningcs.CV

Paper proposes an ensemble model for writer-independent offline signature verification using deep learning.

problem Difficulty in distinguishing genuine signatures from skilled forgeries in writer-independent offline signature verification.

method Used an ensemble model with two CNNs for feature extraction, RGBT for classification, and stacking for final prediction.

result Achieved state-of-the-art performance on various datasets.

Ensemble Learning Deep Learning Offline Signature Verification Feature Extraction Classifier

2019-01-19abs ↗pdf ↗

A writer-independent approach for offline signature verification using deep convolutional neural networks featurescs.CV

Improves signature verification accuracy using deep CNN features.

problem Handwritten signature verification accuracy.

method Deep CNN features combined with writer-independent SVM classifier.

result Proposed approach outperforms other WI-HSV methods.

handwritten signature verification deep CNN writer-independent SVM signature authentication

2018-07-26abs ↗pdf ↗

Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networkscs.CV

Automatic Offline Handwritten Signature Verification has been researched over the last few decades from several perspectives, using insights from graphology, computer vision, signal processing, among others. In spite of the advancements on the field, building classifiers that can separate between genuine signatures and…

2016-04-04abs ↗pdf ↗

Analyzing features learned for Offline Signature Verification using Deep CNNscs.CV

Research on Offline Handwritten Signature Verification explored a large variety of handcrafted feature extractors, ranging from graphology, texture descriptors to interest points. In spite of advancements in the last decades, performance of such systems is still far from optimal when we test the systems against skilled…

2016-07-15abs ↗pdf ↗

Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNscs.CV

Study improves offline signature verification by combining multiple loss functions in CNNs.

problem Challenges in offline signature verification, especially forgeries.

method Examined and integrated cross entropy, Cauchy-Schwarz divergence, and hinge loss into a dynamic multi-loss function.

result Substantial improvements in EERs for writer-dependent OSV protocols.

Offline Signature Verification Convolutional Neural Networks Multi-Loss Function Hinge Loss Cauchy-Schwarz Divergence

2019-03-11abs ↗pdf ↗