activity
20202026
most citedJoint gender and age estimation based on speech signals using x-vectors and transfer learning

10 citations · 23 across the 9 of their papers we have counts for

collaborators

10 papers

eess.AS2026

A corpus-only AUC diagnostic for pooled speech-based depression detection

Cezary Polak, Milosz Dudek, Daria Hemmerling

When clinical speech corpora are pooled for evaluation, corpus membership can itself become predictive if class prevalences differ across sources. We derive the AUC of an oracle pr…

eess.AS2026

Phoneme-Level Mispronunciation Screening in Polish-Speaking Children with an Explainable Assistant

Milosz Dudek, Daria Hemmerling, Kamil Kwarciak +9

Early identification of speech sound errors in children is often limited by access to specialists, motivating lightweight screening tools that can operate outside the clinic. We pr…

eess.IV2024

Automatic Skull Reconstruction by Deep Learnable Symmetry Enforcement

Marek Wodzinski, Mateusz Daniol, Daria Hemmerling

Every year, thousands of people suffer from skull damage and require personalized implants to fill the cranial cavity. Unfortunately, the waiting time for reconstruction surgery ca…

eess.IV2024

Unsupervised Skull Segmentation via Contrastive MR-to-CT Modality Translation

Kamil Kwarciak, Mateusz Daniol, Daria Hemmerling +1

The skull segmentation from CT scans can be seen as an already solved problem. However, in MR this task has a significantly greater complexity due to the presence of soft tissues r…

cs.CV2024★ 1 cited

Improving Deep Learning-based Automatic Cranial Defect Reconstruction by Heavy Data Augmentation: From Image Registration to Latent Diffusion Models

Marek Wodzinski, Kamil Kwarciak, Mateusz Daniol +1

Modeling and manufacturing of personalized cranial implants are important research areas that may decrease the waiting time for patients suffering from cranial damage. The modeling…

eess.IV2024

Automatic Cranial Defect Reconstruction with Self-Supervised Deep Deformable Masked Autoencoders

Marek Wodzinski, Daria Hemmerling, Mateusz Daniol

Thousands of people suffer from cranial injuries every year. They require personalized implants that need to be designed and manufactured before the reconstruction surgery. The man…

cs.HC2024

Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases

Mateusz Daniol, Daria Hemmerling, Jakub Sikora +3

Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for trackin…

eess.IV2023★ 10 cited

High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers

Marek Wodzinski, Mateusz Daniol, Daria Hemmerling +1

Each year thousands of people suffer from various types of cranial injuries and require personalized implants whose manual design is expensive and time-consuming. Therefore, an aut…

eess.IV2022★ 2 cited

Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling

Marek Wodzinski, Mateusz Daniol, Miroslaw Socha +3

The goal of this work is to propose a robust, fast, and fully automatic method for personalized cranial defect reconstruction and implant modeling. We propose a two-step deep learn…

eess.AS2020★ 10 cited

Joint gender and age estimation based on speech signals using x-vectors and transfer learning

Damian Kwasny, Daria Hemmerling

In this paper we extend the x-vector framework for the task of speaker's age estimation and gender classification. In particular, we replace the baseline multilayer-TDNN architectu…