Search Results for author: Vinaychandran Pondenkandath

Found 13 papers, 8 papers with code

Generating Synthetic Handwritten Historical Documents With OCR Constrained GANs

1 code implementation15 Mar 2021 Lars Vögtlin, Manuel Drazyk, Vinaychandran Pondenkandath, Michele Alberti, Rolf Ingold

Second, we transfer the style of a collection of unlabeled historical images to these template documents while preserving their text and layout.

Optical Character Recognition (OCR) Synthetic Data Generation

Labeling, Cutting, Grouping: an Efficient Text Line Segmentation Method for Medieval Manuscripts

1 code implementation11 Jun 2019 Michele Alberti, Lars Vögtlin, Vinaychandran Pondenkandath, Mathias Seuret, Rolf Ingold, Marcus Liwicki

We measured the performance of our method on a recent dataset of challenging medieval manuscripts and surpassed state-of-the-art results by reducing the error by 80. 7%.

Denoising Segmentation +1

A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis

no code implementations22 May 2019 Linda Studer, Michele Alberti, Vinaychandran Pondenkandath, Pinar Goktepe, Thomas Kolonko, Andreas Fischer, Marcus Liwicki, Rolf Ingold

Automatic analysis of scanned historical documents comprises a wide range of image analysis tasks, which are often challenging for machine learning due to a lack of human-annotated learning samples.

General Classification Image Classification +5

Leveraging Random Label Memorization for Unsupervised Pre-Training

no code implementations5 Nov 2018 Vinaychandran Pondenkandath, Michele Alberti, Sammer Puran, Rolf Ingold, Marcus Liwicki

We present a novel approach to leverage large unlabeled datasets by pre-training state-of-the-art deep neural networks on randomly-labeled datasets.

Action Recognition Memorization +2

Offline Signature Verification by Combining Graph Edit Distance and Triplet Networks

1 code implementation17 Oct 2018 Paul Maergner, Vinaychandran Pondenkandath, Michele Alberti, Marcus Liwicki, Kaspar Riesen, Rolf Ingold, Andreas Fischer

Biometric authentication by means of handwritten signatures is a challenging pattern recognition task, which aims to infer a writer model from only a handful of genuine signatures.

Metric Learning

Subword Semantic Hashing for Intent Classification on Small Datasets

3 code implementations16 Oct 2018 Kumar Shridhar, Ayushman Dash, Amit Sahu, Gustav Grund Pihlgren, Pedro Alonso, Vinaychandran Pondenkandath, Gyorgy Kovacs, Foteini Simistira, Marcus Liwicki

In this paper, we introduce the use of Semantic Hashing as embedding for the task of Intent Classification and achieve state-of-the-art performance on three frequently used benchmarks.

Chatbot General Classification +4

Are You Tampering With My Data?

1 code implementation21 Aug 2018 Michele Alberti, Vinaychandran Pondenkandath, Marcel Würsch, Manuel Bouillon, Mathias Seuret, Rolf Ingold, Marcus Liwicki

We propose a novel approach towards adversarial attacks on neural networks (NN), focusing on tampering the data used for training instead of generating attacks on trained models.

DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments

12 code implementations23 Apr 2018 Michele Alberti, Vinaychandran Pondenkandath, Marcel Würsch, Rolf Ingold, Marcus Liwicki

We introduce DeepDIVA: an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality.

Identifying Cross-Depicted Historical Motifs

no code implementations5 Apr 2018 Vinaychandran Pondenkandath, Michele Alberti, Nicole Eichenberger, Rolf Ingold, Marcus Liwicki

Cross-depiction is the problem of identifying the same object even when it is depicted in a variety of manners.

General Classification

Historical Document Image Segmentation with LDA-Initialized Deep Neural Networks

1 code implementation19 Oct 2017 Michele Alberti, Mathias Seuret, Vinaychandran Pondenkandath, Rolf Ingold, Marcus Liwicki

In this paper, we present a novel approach to perform deep neural networks layer-wise weight initialization using Linear Discriminant Analysis (LDA).

Image Segmentation Semantic Segmentation +1

Transforming Sensor Data to the Image Domain for Deep Learning - an Application to Footstep Detection

no code implementations4 Jan 2017 Monit Shah Singh, Vinaychandran Pondenkandath, Bo Zhou, Paul Lukowicz, Marcus Liwicki

Convolutional Neural Networks (CNNs) have become the state-of-the-art in various computer vision tasks, but they are still premature for most sensor data, especially in pervasive and wearable computing.

General Classification Transfer Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.