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Publicações

2024

On the Human-AI Metaphorical Interplay for Culturally Sensitive Generative AI Design in Music Co-Creation

Autores
Correia A.;

Publicação
CEUR Workshop Proceedings

Abstract
This research revolves around the potential challenges, opportunities, and strategies associated with human-centered generative artificial intelligence (AI) in the music compositional practice, emphasizing the role of metaphorical design in shaping musicians' expectations toward the adoption of generative AI in their everyday creative activities. Through a human-computer interaction (HCI) lens, this paper aims to discuss the cultural implications of the human-AI metaphorical design space for the seamless integration of intelligent algorithmic experiences in a manner that aligns with cultural values and realistic expectations of music creators while promoting informed policies, sociotechnical imaginaries, and culturally sensitive generative AI design strategies with focus on user-friendly interfaces that resonate with diverse music creation groups.

2024

Synthetic Aperture Radar in Vineyard Monitoring: Examples, Demonstrations, and Future Perspectives

Autores
Bakon, M; Teixeira, AC; Padua, L; Morais, R; Papco, J; Kubica, L; Rovnak, M; Perissin, D; Sousa, JJ;

Publicação
REMOTE SENSING

Abstract
Synthetic aperture radar (SAR) technology has emerged as a pivotal tool in viticulture, offering unique capabilities for various applications. This study provides a comprehensive overview of the current state-of-the-art applications of SAR in viticulture, highlighting its significance in addressing key challenges and enhancing viticultural practices. The historical evolution and motivations behind SAR technology are also provided, along with a demonstration of its applications within viticulture, showcasing its effectiveness in various aspects of vineyard management, including delineating vineyard boundaries, assessing grapevine health, and optimizing irrigation strategies. Furthermore, future perspectives and trends in SAR applications in viticulture are discussed, including advancements in SAR technology, integration with other remote sensing techniques, and the potential for enhanced data analytics and decision support systems. Through this article, a comprehensive understanding of the role of SAR in viticulture is provided, along with inspiration for future research endeavors in this rapidly evolving field, contributing to the sustainable development and optimization of vineyard management practices.

2024

Programming Mobile Robots in an Educational Context: a Hardware-in-the-loop Approach

Autores
Brancaliao, L; Alvarez, M; Coelho, J; Conde, M; Costa, P; Goncalves, J;

Publicação
2024 10TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES, CODIT 2024

Abstract
In this paper it is presented a Hardware-in-theloop (HIL) mobile robot programming approach, to be applied in a robotics educational context. The motivation to apply this approach is the fact that students can program the robots without access to the robot hardware, but still maintain some important closed loop control critical features, such as a realistic lag time and the possibility for a larger number of students to program at the same time. Therefore, the developed software is applied to the real hardware without any change. The HIL approach was applied to provide a simulation close to reality, once the processing occurs in the real robot processor and the actuation and sensorization inside the simulation, adding to the advantage to test the firmware avoiding damage in the physical robot.

2024

Augmented Reality for Spectral Imaging Applications

Autores
Cavaco, R; Lopes, T; Jorge, PAS; Silva, NA;

Publicação
UNCONVENTIONAL OPTICAL IMAGING IV

Abstract
Spectral imaging is a technique that captures spectral information from a scene and maps it onto a 2D image, featuring the potential to reveal hidden features and properties of objects that are invisible to the human eye, such as elemental and molecular compositions. Augmented reality (AR), on the other hand, is a technology that enhances the perception of reality by superimposing digital information on the physical world. While these technologies have different purposes, they can be considered one and the same in terms of providing an user-centric extension of reality. Spectral imaging provides the information that can reveal the underlying nature of objects, while AR provides the method of visualization that can display the information in an intuitive and interactive way. In this work, we present a novel Unity toolkit that combines spectral imaging and a HoloLens 2 AR device to create an interactive and immersive experience for the user. The toolkit enables the interactive visualization of various elemental maps of a 3D rock model in AR using a simple and intuitive interface. With this technique, the user can select a sample model and an elemental map from a preloaded asset library and then see the map projected onto the rock model in AR, using simple interactions such as zoom adjustment, rotation, and pan of the models to explore features and properties in detail. The toolkit offers several advantages, including better contextual interpretation of the spectral data by placing it in relation to the shape and texture of the rock, increased user engagement and curiosity through the creation of a realistic and immersive experience, and ease of decision-making through the provision of comparative tools. In short, by combining spectral imaging and AR, we present an innovative approach that can enrich the user experience and expand the user knowledge of the environment.

2024

A Tight Security Proof for SPHINCS+, Formally Verified

Autores
Barbosa, M; Dupressoir, F; Hülsing, A; Meijers, M; Strub, PY;

Publicação
Advances in Cryptology - ASIACRYPT 2024 - 30th International Conference on the Theory and Application of Cryptology and Information Security, Kolkata, India, December 9-13, 2024, Proceedings, Part IV

Abstract

2024

MedShapeNet - a large-scale dataset of 3D medical shapes for computer vision

Autores
Li, JN; Zhou, ZW; Yang, JC; Pepe, A; Gsaxner, C; Luijten, G; Qu, CY; Zhang, TZ; Chen, XX; Li, WX; Wodzinski, M; Friedrich, P; Xie, KX; Jin, Y; Ambigapathy, N; Nasca, E; Solak, N; Melito, GM; Vu, VD; Memon, AR; Schlachta, C; De Ribaupierre, S; Patel, R; Eagleson, R; Chen, XJ; Mächler, H; Kirschke, JS; de la Rosa, E; Christ, PF; Li, HB; Ellis, DG; Aizenberg, MR; Gatidis, S; Küstner, T; Shusharina, N; Heller, N; Andrearczyk, V; Depeursinge, A; Hatt, M; Sekuboyina, A; Löffler, MT; Liebl, H; Dorent, R; Vercauteren, T; Shapey, J; Kujawa, A; Cornelissen, S; Langenhuizen, P; Ben-Hamadou, A; Rekik, A; Pujades, S; Boyer, E; Bolelli, F; Grana, C; Lumetti, L; Salehi, H; Ma, J; Zhang, Y; Gharleghi, R; Beier, S; Sowmya, A; Garza-Villarreal, EA; Balducci, T; Angeles-Valdez, D; Souza, R; Rittner, L; Frayne, R; Ji, YF; Ferrari, V; Chatterjee, S; Dubost, F; Schreiber, S; Mattern, H; Speck, O; Haehn, D; John, C; Nürnberger, A; Pedrosa, J; Ferreira, C; Aresta, G; Cunha, A; Campilho, A; Suter, Y; Garcia, J; Lalande, A; Vandenbossche, V; Van Oevelen, A; Duquesne, K; Mekhzoum, H; Vandemeulebroucke, J; Audenaert, E; Krebs, C; van Leeuwen, T; Vereecke, E; Heidemeyer, H; Röhrig, R; Hölzle, F; Badeli, V; Krieger, K; Gunzer, M; Chen, JX; van Meegdenburg, T; Dada, A; Balzer, M; Fragemann, J; Jonske, F; Rempe, M; Malorodov, S; Bahnsen, FH; Seibold, C; Jaus, A; Marinov, Z; Jaeger, PF; Stiefelhagen, R; Santos, AS; Lindo, M; Ferreira, A; Alves, V; Kamp, M; Abourayya, A; Nensa, F; Hörst, F; Brehmer, A; Heine, L; Hanusrichter, Y; Wessling, M; Dudda, M; Podleska, LE; Fink, MA; Keyl, J; Tserpes, K; Kim, MS; Elhabian, S; Lamecker, H; Zukic, D; Paniagua, B; Wachinger, C; Urschler, M; Duong, L; Wasserthal, J; Hoyer, PF; Basu, O; Maal, T; Witjes, MJH; Schiele, G; Chang, TC; Ahmadi, SA; Luo, P; Menze, B; Reyes, M; Deserno, TM; Davatzikos, C; Puladi, B; Fua, P; Yuille, AL; Kleesiek, J; Egger, J;

Publicação
BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK

Abstract
Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models). However, a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instruments is missing. Methods: We present MedShapeNet to translate data-driven vision algorithms to medical applications and to adapt state-of-the-art vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. We present use cases in classifying brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. Results: By now, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Conclusions: MedShapeNet contains medical shapes from anatomy and surgical instruments and will continue to collect data for benchmarks and applications. The project page is: https://medshapenet.ikim.nrw/.

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