Deep neural network models are commonly used in computer vision problems, e.g., image segmentation. Convolutional neural networks have been state-of-the-art methods in image processing, but new architectures, such as ...
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ISBN:
(纸本)9783031637858;9783031637834
Deep neural network models are commonly used in computer vision problems, e.g., image segmentation. Convolutional neural networks have been state-of-the-art methods in image processing, but new architectures, such as Transformer-based approaches, have started outperforming previous techniques in many applications. However, those techniques are still not commonly used in urban analyses, mostly performed manually. This paper presents a framework for the residential building semantic segmentation architecture as a tool for automatic urban phenomena monitoring. The method could improve urban decision-making processes with automatic city analysis, which is predisposed to be faster and even more accurate than those made by human researchers. The study compares the application of new deep network architectures with state-of-the-art solutions. The analysed problem is urban functional zone segmentation for the urban sprawl evaluation using targeted land cover map construction. The proposed method monitors the expansion of the city, which, uncontrolled, can cause adverse effects. The method was tested on photos from three residential districts. The first district has been manually segmented by functional zones and used for model training and evaluation. The other two districts have been used for automated segmentation by models' inference to test the robustness of the methodology. The test resulted in 98.2% accuracy.
The scene text retrieval system can search all the images containing the query text in the gallery based on the input query text and locate the position of the query text at the same time. The current state-...
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Internet of Things (IoT) devices are ubiquitous in modern society, the device identity and authentication schemes are playing a fundamental role in IoT system protection. However, the existing schemes face challenges ...
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Defining script types and establishing classification criteria for medieval handwriting is a central aspect of palaeographical analysis. However, existing typologies often encounter methodological challenges, such as ...
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ISBN:
(纸本)9783031706417;9783031706424
Defining script types and establishing classification criteria for medieval handwriting is a central aspect of palaeographical analysis. However, existing typologies often encounter methodological challenges, such as descriptive limitations and subjective criteria. We propose an interpretable deep learning-based approach to morphological script type analysis, which enables systematic and objective analysis and contributes to bridging the gap between qualitative observations and quantitative measurements. More precisely, we adapt a deep instance segmentation method to learn comparable character prototypes, representative of letter morphology, and provide qualitative and quantitative tools for their comparison and analysis. We demonstrate our approach by applying it to the Textualis Formata script type and its two subtypes formalized by A. Derolez: Northern and Southern Textualis.
An air writing alphabet recognition system based on the images of temporal spectrogram such as average range-time map, average Doppler-time map and average angle-time map derived from an mmWave FMCW radar is proposed....
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This study introduces an innovative virtual reality (VR) training system for novice fencers, aimed at improving their offensive actions, distance perception, and overall combat performance. The system is divided into ...
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Neural topic models (NTMs) have shown their success in topic modeling with a wide range of applications in text analysis. NTMs based on generative models prioritize document representations with good reconstruction ca...
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Using serious games to teach project management is a logical choice, as it al-lows students to practice skills without facing real-world economic or human consequences. These games offer a realistic learning environme...
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For medical images, domain shift is a very common phenomenon. To address this issue, researchers have proposed unsupervised domain adaptation and multi-source domain generalization. However, these methods are sometime...
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Multimodal Sentiment Analysis (MSA) is a popular research field in natural language processing and affective computing. Recent works have shown the feasibility of Multimodal Large Language Models (MLLMs) for zero-shot...
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