Wyszukiwarka
dr inż. Sebastian Cygert
Zatrudnienie
- Specjalista informatyk w Katedra Systemów Multimedialnych
- Adiunkt w Katedra Systemów Multimedialnych
Publikacje
Filtry
wszystkich: 30
Katalog Publikacji
Rok 2024
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublikacjaIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
Rok 2021
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublikacjaWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Robustness in Compressed Neural Networks for Object Detection
PublikacjaModel compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...
Rok 2019
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Comparative study on the effectiveness of various types of road traffic intensity detectors
PublikacjaVehicle detection and speed measurements are crucial tasks in traffic monitoring systems. In this work, we focus on several types of electronic sensors, operating on different physical principles in order to compare their effectiveness in real traffic conditions. Commercial solutions are based on road tubes, microwave sensors, LiDARs, and video cameras. Distributed traffic monitoring systems require a high number of monitoring...
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Recovering Sound Produced by Wind Turbine Structures Employing Video Motion Magnification
PublikacjaThe recordings were made with a fast video camera and with a microphone. Using fast cameras allowed for observation of the micro vibrations of the object structure. Motion-magnified video recordings of wind turbines on a wind farm were made for the purpose of building a damage prediction system. An idea was to use video to recover sound & vibrations in order to obtain a contactless diagnostic method for wind turbines. The recovered signals...
Rok 2022
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Creating new voices using normalizing flows
PublikacjaCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
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Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
Rok 2023
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Cross-Lingual Knowledge Distillation via Flow-Based Voice Conversion for Robust Polyglot Text-to-Speech
PublikacjaIn this work, we introduce a framework for cross-lingual speech synthesis, which involves an upstream Voice Conversion (VC) model and a downstream Text-To-Speech (TTS) model. The proposed framework consists of 4 stages. In the first two stages, we use a VC model to convert utterances in the target locale to the voice of the target speaker. In the third stage, the converted data is combined with the linguistic features and durations...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
Rok 2018
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Eulerian motion magnification applied to structural health monitoring of wind turbines
PublikacjaSeveral types of defects may occur in wind turbines, as physical damage of blades or gearbox malfunction. A wind farm monitoring and damage prediction system is built to observe abnormal vibrations of elements of wind turbine: blades, nacelle, and tower. Contactless methods are developed which do not require turbine stopping. In this work, structural health monitoring of a wind turbine is evaluated using a conversion from the captured...
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REJESTRACJA, PARAMETRYZACJA I KLASYFIKACJA ALOFONÓW Z WYKORZYSTANIEM BIMODALNOŚCI
PublikacjaPraca dotyczy rejestracji i parametryzacji alofonów w języku angielskim z wykorzystaniem dwóch modalności. W badaniach dokonano rejestracji wypowiedzi w języku angielskim mówców, których znajomość tego języka odpowiada poziomowi rodowitego mówcy. W kolejnym etapie wyodrębnione zostały alofony z nagrań fonicznych i odpowiadające im sygnały wizyjne. W procesie tworzenia wektorów cech wykorzystano odrębne systemy parametryzacji,...
Rok 2020
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Evaluating calibration and robustness of pedestrian detectors
PublikacjaIn this work robustness and calibration of modern pedestrian detectors are evaluated. Pedestrian detection is a crucial perception com- ponent in autonomous driving and here we study its performance under different image corruptions. Furthermore, we provide analysis of classifi- cation calibration of pedestrian detectors and we show a positive effect of using style-transfer augmentation technique. Our analysis is aimed as a step...
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Evaluating Calibration and Robustness of Pedestrian Detectors
Publikacja
Rok 2014
Rok 2017
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Shape-Based Pose Estimation of Robotic Surgical Instruments
PublikacjaWe describe a detector of robotic instrument parts in image-guided surgery. The detector consists of a huge ensemble of scale-variant and pose-dedicated, rigid appearance templates. The templates, which are equipped with pose-related keypoints and segmentation masks, allow for explicit pose estimation and segmentation of multiple end-effectors as well as fine-grained non-maximum suppression. We train the templates by grouping examples...
wyświetlono 973 razy