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Browsing by Issue Date, starting with "2025-11-12"

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  • Piano a quatro mãos como estratégia pedagógica na formação de pianistas
    Publication . Santos, Ana Isabel da Silva; Coelho, Luís Miguel Carvalhais Figueiredo Borges; Resende, Eduardo; Madeira, Lígia; McTait, Trevor
    O presente relatório remete para o trabalho desenvolvido durante a Prática de Ensino Supervisionada, realizada na Escola Profissional de Música de Espinho, no âmbito do Mestrado em Ensino de Música, da Escola Superior de Música e Artes do Espetáculo do Porto (ESMAEIPP). Propõe-se apresentar uma reflexão sobre a prática pedagógica, ao longo de dois capítulos. O terceiro capítulo expõe a investigação de natureza qualitativa, desenvolvido num módulo experimental de oito semanas de duração, que examinou os efeitos da prática de piano a quatro mãos enquanto ferramenta pedagógica no progresso técnico, interpretativo e socioemocional de seis estudantes. A reflexão final articula a pertinência do estudo com o trabalho desenvolvido durante a PES.
    2025-11-12Master thesis Open access Show more
  • A voz dos corpos que gritam
    Publication . Marques, Catarina Isabel Rapazinho; Silva, Carolina Lyra Barros da
    Esta monografia reflete sobre a pesquisa e prática do projeto A Voz dos Corpos que Gritam, apresentado em maio de 2025 na Escola Superior de Música e Artes do Espectáculo, através de uma Mostra Corpos Fragmentados e Vozes Fluidas, que incluiu a performance e a exposição do processo. A investigação surge do desejo de explorar a insegurança feminina e como heranças comportamentais moldam a forma de viver de mulheres e homens. A pesquisa articula mitologia, práticas artísticas e laboratórios coletivos, integrando momentos autobiográficos e questionando a liberdade de Ser. Ao longo do processo, heranças culturais são ressignificadas ou deixadas de lado, permitindo explorar diferentes caminhos de expressão da identidade e da feminilidade através da arte.
    2025-11-12Master thesis Restricted access Show more
  • Computer Vision for Image-Based Automated Analogue Gauge Reading
    Publication . ABREU, DIOGO PAUPÉRIO ANTÓNIO DE; Viana, Paula Maria Marques Moura Gomes
    Analogue gauges display physical quantities through a needle over a marked scale and remain common in vehicles, medical devices, and industrial systems. In practice, readings are often recorded on site by a human operator. Replacing all gauges with networked sensors is possible but typically costly and disruptive. We developed a lightweight on-device system based on computer vision and machine learning. The pipeline operates in two stages. First, it detects the gauge within an image. Second, it estimates the value using ellipse and needle geometry combined with optical character recognition (OCR) and a robust angle-to-value mapping. The system runs fully offline on a mobile device, following a privacy-by-design approach: images remain on the device, no raw frames or identifiers are transmitted, and intermediate data are kept only for local inference. All quantitative results presented here refer to the desktop pipeline. The mobile application demonstrates on-device feasibility but is not benchmarked for accuracy or latency in this work. Two complementary datasets were used for evaluation. The Tailored Test Set contains controlled images with known pose, where the needle is rotated through fixed angles, and is used to stress-test the reading stage under standardised conditions. The Unfiltered Test Set contains real and heterogeneous images with unknown orientation and scale, and is used to evaluate the complete pipeline under unconstrained conditions. For detection, YOLOv5-Lite-S was trained on the largest dataset used in this research compared to prior work, combining about ten thousand synthetic images with more than seven hundred real ones. This mixed training improved performance on a real-world benchmark of 568 images from mAP0.50:0.95 = 30.2% to 36.8%, with mAP0.50 = 82.7%. In task-based evaluation, the model achieved a mean detection rate of Rdetection = 91.3% on the Unfiltered Test Set and 100% on the Tailored Test Set. On a shared subset from a prior benchmark, the detector reached 100% detection versus 98.6% previously reported. For reading, the end-to-end pipeline completed 91.8% of cases on the Tailored set and 82.7% on the Unfiltered set. Within the Unfiltered set, 46.3% of all images — corresponding to 56.0% of completed reads — were within ±5% of full scale. On matched gauges, the system outperformed prior results in most metrics, including black-dial cases that are typically difficult due to low contrast and sparse labels, although unconstrained reading accuracy did not exceed the best published results in every scenario. The system is deployable, privacy-preserving, and has a low computational footprint, which is valuable where processing, connectivity, or data governance constraints limit cloud-based solutions. We also explored large multimodal models to assess their potential for understanding scale limits and units. Without any fine-tuning, the model correctly identified minimum and maximum values and units in 81.8% of gauges, though it was not integrated into the pipeline, final readings still rely on classical computer vision. In summary, a fully automatic detector–reader can be built with modest computational resources. Mixing synthetic and real data improves detection on real images. Reading is reliable under standardised conditions and feasible under unconstrained ones, with accuracy mainly limited by OCR quality and label sparsity. Future work should focus on on-device benchmarking, increased robustness, and integration of more advanced OCR or multimodal models.
    2025-11-12Master thesis Embargoed access Show more