Publications related to Lausanne Historical Censuses Dataset HTR 35k

Related publications (32)

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

Touradj Ebrahimi, Michela Testolina, Davi Nachtigall Lazzarotto

The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...

Springer2024

Post-correction of Historical Text Transcripts with Large Language Models: An Exploratory Study

Frédéric Kaplan, Maud Ehrmann, Matteo Romanello, Sven Nicolas Yoann Najem-Meyer, Emanuela Boros

The quality of automatic transcription of heritage documents, whether from printed, manuscripts or audio sources, has a decisive impact on the ability to search and process historical texts. Although significant progress has been made in text recognition ( ...

Association for Computational Linguistics2024

1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History

Isabella Di Lenardo, Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo, Marion Kramer

This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 mi ...

Zenodo2023

Communication-efficient distributed training of machine learning models

Thijs Vogels

In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...

EPFL2023

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

EPFL2023

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Touradj Ebrahimi

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

IEEE COMPUTER SOC2023

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Touradj Ebrahimi, Michela Testolina, Evgeniy Upenik

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

2023

An end-to-end pipeline for historical censuses processing

Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo, Marion Kramer

Censuses are structured documents of great value for social and demographic history, which became widespread from the nineteenth century on. However, the plurality of formats and the natural variability of historical data make their extraction arduous and ...

2023

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

Explanation of Face Recognition via Saliency Maps

Touradj Ebrahimi, Yuhang Lu

Despite the significant progress in recent years, deep face recognition is often treated as a "black box" and has been criticized for lacking explainability. It becomes increasingly important to understand the characteristics and decisions of deep face rec ...

2023

Regularization of polynomial networks for image recognition

Volkan Cevher, Grigorios Chrysos, Bohan Wang

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...

2023

Regularization of polynomial networks for image recognition

Volkan Cevher, Grigorios Chrysos, Bohan Wang

Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...

Ieee Computer Soc2023

ms3: A parser for MuseScore files, serving as data factory for annotated music corpora

Martin Alois Rohrmeier, Johannes Hentschel

The Python library ms3 makes scores (symbolic representations of music) operational for computational approaches by representing their contents as sets of tabular files. Music scores represent relations between sounding events by graphical means. The Free ...

2023

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Mathias Josef Payer, Chunmin Zhang, Zhiyao Feng

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Usenix Assoc2023

From Archival Sources to Structured Historical Information: Annotating and Exploring the "Accordi dei Garzoni"

Orlin Biserov Topalov, Frédéric Kaplan, Maud Ehrmann

If automatic document processing techniques have achieved a certain maturity for present time documents, the transformation of hand-written documents into well-represented, structured and connected data which can satisfactorily be used for historical study ...

Routledge, Taylor & Francis Group2023

Dense Image-based Predictions for Comics Analysis

Deblina Bhattacharjee

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

EPFL2023

Gospel of the Marseille Docker - Nicholas Derybolsky from 1952

Sila Karatas

This text, accompanied by a ‘gospel’ that I made by montaging the US-recorded captions, is an attempt for re-narrating Marshall Plan’s discourse on the working class, aka the so-called ‘free labor’ of the US against the ‘communist labor’ of the “Soviet thr ...

EPFL Press2023

Evaluating the effect of sparse convolutions on point cloud compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...

2023

Sparse Autoencoders for Speech Modeling and Recognition

Selen Hande Kabil

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

EPFL2023

Unsupervised Term Extraction for Highly Technical Domains

Diego Matteo Antognini

Term extraction is an information extraction task at the root of knowledge discovery platforms. Developing term extractors that are able to generalize across very diverse and potentially highly technical domains is challenging, as annotations for domains r ...

2022