This book constitutes the refereed proceedings of the 17th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2022, held in Salamanca, Spain, in September 2022.;The 43 full papers presented in thi...
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ISBN:
(数字)9783031154713
ISBN:
(纸本)9783031154706
This book constitutes the refereed proceedings of the 17th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2022, held in Salamanca, Spain, in September 2022.;The 43 full papers presented in this book were carefully reviewed and selected from 67 submissions. They were organized in topical sections as follows: bioinformatics; data mining and decision support systems; deep learning; evolutionary computation; HAIS applications; image and speech signal processing; and optimization techniques.
This book constitutes the refereed proceedings of the 18th Conference of the Spanish Association for;Artificial Intelligence, CAEPIA 2018, held in Granada, Spain, in October 2018.;The 36 full papers presented w...
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ISBN:
(数字)9783030003746
ISBN:
(纸本)9783030003739
This book constitutes the refereed proceedings of the 18th Conference of the Spanish Association for;Artificial Intelligence, CAEPIA 2018, held in Granada, Spain, in October 2018.;The 36 full papers presented were carefully selected from 240 submissions. The Conference of the Spanish Association of;Artificial Intelligence (CAEPIA) is a biennial forum open to researchers from all over the world to present and discuss their latest scientific and technological advances in Antificial Intelligence (AI). Authors are kindly requested to submit unpublished original papers describing relevant research on AI issues from all points of view: formal, methodological, technical or applied.
Body joint modeling and human pose reconstruction provide precise motion and quantitative geometric information about human dynamics. The rich motion information obtained from human pose estimation plays important rol...
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Body joint modeling and human pose reconstruction provide precise motion and quantitative geometric information about human dynamics. The rich motion information obtained from human pose estimation plays important roles in a wide range of digital twin and connected health applications. However, current related researches have difficulties in extracting the joints’ spatial-temporal correlations from different levels. This is due to the poses being at various complexities in moving various joints differently. Hence, the typical conventional transformer method is non-adaptable and barely meets the aforementioned requirement. In this paper, we propose the Body Joint Interactive transFormers (BJIFormer) to extract the multi-level joints’ spatial-temporal information. The design enables the model to learn the inner joints’ correlation inside the body parts across frames and propagate the extracted information across the body parts with shared joints. The multi-level body joint interactive scheme has greater efficiency improvement by restricting the self-attention computation to partial body parts and connecting each body part by torso. The proposed interactive approach explores the spatial-temporal correlation following the hierarchical paradigm and effectively estimates and reconstructs 3D human poses.
Most contemporary work on magnetic tunnel junctions either consider ballistic quantum transport across the tunneling barrer, for instance via the Non Equilibrium Green's Function (NEGF) formalism, or treat the tun...
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We theoretically study the spin-dependent transport of conduction electrons across typical metal/semiconductor (SC)/metal structures, where the SC channel exhibits Rashba spin-orbit coupling (SOC) and the metal contac...
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