Titlebook: Deep Learning Theory and Applications; 5th International Co Ana Fred,Allel Hadjali,Carlo Sansone Conference proceedings 2024 The Editor(s)

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Conference proceedings 2024ions, DeLTA 2024, which took place in Dijon, France, during July 10-11, 2024.?..The 44 papers included in these proceedings were carefully reviewed and selected from a total of 70 submissions. They focus on topics such as deep learning and big data analytics; machine-learning and artificial intellig

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1865-0929 eviewed and selected from a total of 70 submissions. They focus on topics such as deep learning and big data analytics; machine-learning and artificial intelligence, etc.?.978-3-031-66693-3978-3-031-66694-0Series ISSN 1865-0929 Series E-ISSN 1865-0937

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Erleichterung der Schuldenlast,ents show that the presented approach works for various human motions and input representations, such as the SMPL pose parameters, trajectory data, and skeleton joints. We achieve higher accuracy compared to the state-of-the-art methods on all three datasets.

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larity, resulting in imbalanced datasets for training deep-learning models. To address this issue, a class balancing technique is proposed and applied to all datasets to improve consistency and results. Ensemble techniques are utilized to combine all of the model predictions to produce the highest F1-scores for all three labels.

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Action Conditioned Attention Encoder-Decoder and?Discriminator for?Human Motion Generationents show that the presented approach works for various human motions and input representations, such as the SMPL pose parameters, trajectory data, and skeleton joints. We achieve higher accuracy compared to the state-of-the-art methods on all three datasets.

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A Deep Learning-Based Plant Disease Detection and Classification for Arabica Coffee Leavess reducing the yield and adversely affecting the quality of the coffee. Detecting and controlling these diseases in their early stages represent formidable challenges, since traditional methods rely on visual observation by experts and often fail in accurate diagnosis. Machine learning (ML) techniqu

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