Książki, monografie, podręczniki, rozdziały (WEEIiA)

Stały URI dla kolekcjihttp://hdl.handle.net/11652/171

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2021 - 202424

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Data rozpoczęcia: 2020Data zakończenia: 2024

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Teraz wyświetlane 1 - 10 z 24
  • Pozycja
    Nasze życie, doświadczenie, pasje...50 lat minęło..."Złoty dyplom" 1972-2022
    (Wydawnictwo Politechniki Łódzkiej, 2024) Mosiński, Franciszek. Red.; Ronke, Jerzy. Red.; Starzak, Stanisław
  • Pozycja
    Distribution
    (Wydawnictwo Politechniki Łódzkiej, 2023) Laska-Leśniewicz, Anna
  • Pozycja
    Introduction
    (Wydawnictwo Politechniki Łódzkiej, 2023) Laska-Leśniewicz, Anna; Malinowska-Olszowy, Monika
  • Pozycja
    Sustainable development and circular economy
    (Wydawnictwo Politechniki Łódzkiej, 2023) Laska-Leśniewicz, Anna; Malinowska-Olszowy, Monika
  • Pozycja
    Sustainable design and process in textiles for higher education
    (Wydawnictwo Politechniki Łódzkiej, 2023) Malinowska-Olszowy, Monika (Red.); Laska-Leśniewicz, Anna (Red.); Glogar, Martinia, Ira (Rec.)
    "The E-Book on Sustainable Design and Process in Textiles is one of the several types of educational activities undertaken in the GreenTEX project. To the best authors‘ knowledge, it is necessary to change the awareness and approach to sustainability in the broad textile industry (and related ones). Future textile designers who in the future will create new products and solutions not only for the textile and clothing industry but also for others that use textile products (such as medicine, transport, hygiene industry and protective equipment) must have full knowledge and awareness of how to create new solutions in line with the goals of sustainable development. [...]"
  • Pozycja
    Predictive User Interface for Emerging Experiences
    (Wydawnictwo Politechniki Łódzkiej, 2023) Kapusta, Paweł; Duch, Piotr
    This research paper focuses on the use of predictive techniques to improve interaction with user interfaces in emerging experiences such as Virtual Reality, Augmented Reality, Metaverse, and touchless kiosks and dashboards. We propose the concept of intelligent snapping, which uses gaze tracking, head-pose tracking, hand tracking, as well as gesture recognition and hand posture recognition to catch the intent of the person rather than the actual input.
  • Pozycja
    Grounded HyperSymbolic Representations Learned through Gradient-Based Optimization
    (Wydawnictwo Politechniki Łódzkiej, 2023) Łuczak, Piotr; Ślot, Krzysztof; Kucharski, Jacek
    Hyperdimensional computing is a novel paradigm, capable of processing complex data structures with simple operations. Its main limitations lie in the conversion of real world data onto hyperdimensional space, which due to lack of a universal translation scheme, oftentimes requires application-specific methods. This work presents a novel method for unsupervised hyperdimensional conversion of arbitrary image data. Additionally, this method is augmented by the ability of creating HyperSymbols, or class prototypes, provided that such class labels are available. The proposed method achieves promising performance on MNIST dataset, both in translating individual samples as well as producing HyperSymbols for downstream classification task.
  • Pozycja
    Autoregressive Label-Conditioned Autoencoder for Controllable Image-To-Video Generation
    (Wydawnictwo Politechniki Łódzkiej, 2023) Kubicki, Kacper; Ślot, Krzysztof
    Generating videos from a single image with user-controlled attributes is a complex challenge in the field of computer vision, despite the significant advancements recently made in the field. This paper presents a novel approach to tackle this issue, leveraging a convolutional autoencoder with supervised principal component analysis and autoregressive inference step. The efficacy of the proposed method is evaluated on two datasets – MNIST handwritten-digits and time-lapse photos of the sky. Results from both quantitative and qualitative analyses show that the proposed approach produces high-quality videos of variable duration with user-defined attributes, while preserving the integrity of original image contents.
  • Pozycja
    A Convolutional and Recurrent Neural Network-based Approach for Speech Emotion Recognition
    (Wydawnictwo Politechniki Łódzkiej, 2023) Duch, Piotr; Wiatrowska, Izabela; Kapusta, Paweł
    Speech emotion recognition (SER) is a crucial aspect of humancomputer interaction. In this article, we propose a deep learning approach, using CNN and RNN architectures, for SER using both convolutional and recurrent neural networks. We evaluated the approach on four audio datasets, including CREMA-D, RAVDESS, TESS, and EMOVO. Our experiments tested various feature sets and extraction settings to determine optimal features for SER. Our results demonstrate that the proposed approach achieves high accuracy rates and outperforms state-of-the-art algorithms.
  • Pozycja
    RNN-based Phase Unwrapping for Enabling Vital Parameter Monitoring with FMCW Radars
    (Wydawnictwo Politechniki Łódzkiej, 2023) Łuczak, Piotr; Hausman, Sławomir; Ślot, Krzysztof
    Application of radar technology enables remote breathing and heart rate monitoring by analyzing motion waveforms, which are reconstructed from phase signals extracted from radar-delivered data. However, nonlinear deformations introduced by phase recovery procedure make accurate motion reconstruction highly challenging, especially for millimeter-long waves that are commonly generated by state-of-the-art radar devices. In the presented paper we show that a GRU-based neural predictor is capable of correct phase unwrapping under presence of noise (originating e.g. from random subject’s movements), enabling vital parameter monitoring in realistic scenarios, which cannot be accomplished using standard approaches.