arXiv subjects

Jan Cychnerski

Publications and source records attributed to Jan Cychnerski.

2 recordsLinked to original sources

arXiv2023

Architecture Design of a Networked Music Performance Platform for a Chamber Choir

This paper describes an architecture design process for Networked Music Performance (NMP) platform for medium-sized conducted music ensembles, based on remote rehearsals of Academic Choir of Gdansk University of Technology. The issues of real-time remote communication, in-person music performance, and NMP are described. Three iterative steps defining and extending the architecture of the NMP platform with additional features to enhance its utility in remote rehearsals are presented. The first iteration uses a regular video conferencing platform, the second iteration uses dedicated NMP devices and tools, and the third iteration adds video transmission and utilizes professional low-latency audio and video workstations. For each iteration, the platform architecture is defined and deployed with simultaneous usability tests. Its strengths and weaknesses are identified through qualitative and quantitative measurements - statistical analysis shows a significant improvement in rehearsal quality after each iteration. The final optimal architecture is described and concluded with guidelines for creating NMP systems for said music ensembles.

cs.NI↗

arXiv2022

ERS: a novel comprehensive endoscopy image dataset for machine learning, compliant with the MST 3.0 specification

The article presents a new multi-label comprehensive image dataset from flexible endoscopy, colonoscopy and capsule endoscopy, named ERS. The collection has been labeled according to the full medical specification of 'Minimum Standard Terminology 3.0' (MST 3.0), describing all possible findings in the gastrointestinal tract (104 possible labels), extended with an additional 19 labels useful in common machine learning applications. The dataset contains around 6000 precisely and 115,000 approximately labeled frames from endoscopy videos, 3600 precise and 22,600 approximate segmentation masks, and 1.23 million unlabeled frames from flexible and capsule endoscopy videos. The labeled data cover almost entirely the MST 3.0 standard. The data came from 1520 videos of 1135 patients. Additionally, this paper proposes and describes four exemplary experiments in gastrointestinal image classification task performed using the created dataset. The obtained results indicate the high usefulness and flexibility of the dataset in training and testing machine learning algorithms in the field of endoscopic data analysis.

cs.CV↗