Deep Learning Theory and Applications
5th International Conference, DeLTA 2024, Dijon, France, July 10¿11, 2024, Proceedings, Part I
Herausgegeben:Fred, Ana; Hadjali, Allel; Gusikhin, Oleg; Sansone, Carlo
Deep Learning Theory and Applications
5th International Conference, DeLTA 2024, Dijon, France, July 10¿11, 2024, Proceedings, Part I
Herausgegeben:Fred, Ana; Hadjali, Allel; Gusikhin, Oleg; Sansone, Carlo
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The two-volume set CCIS 2171 and 2172 constitutes the refereed best papers from the 5th International Conference on Deep Learning Theory and Applications, 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 intelligence, etc.
- Deep Learning Theory and Applications55,99 €
- Deep Learning Theory and Applications48,99 €
- Deep Learning Theory and Applications48,99 €
- Charu C. AggarwalNeural Networks and Deep Learning50,79 €
- Charu C. AggarwalNeural Networks and Deep Learning63,99 €
- Charu C. AggarwalNeural Networks and Deep Learning37,99 €
- Deep Learning Theory and Applications59,99 €
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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 intelligence, etc.
- Produktdetails
- Communications in Computer and Information Science 2171
- Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
- Artikelnr. des Verlages: 978-3-031-66693-3
- 2024
- Seitenzahl: 392
- Erscheinungstermin: 21. August 2024
- Englisch
- Abmessung: 235mm x 155mm x 22mm
- Gewicht: 593g
- ISBN-13: 9783031666933
- ISBN-10: 3031666933
- Artikelnr.: 70976734
- Communications in Computer and Information Science 2171
- Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
- Artikelnr. des Verlages: 978-3-031-66693-3
- 2024
- Seitenzahl: 392
- Erscheinungstermin: 21. August 2024
- Englisch
- Abmessung: 235mm x 155mm x 22mm
- Gewicht: 593g
- ISBN-13: 9783031666933
- ISBN-10: 3031666933
- Artikelnr.: 70976734
Learning: Performance Comparison Between N-Gram and TF-IDF.- Evolving Deep Architectures: A New Blend of CNNs and Transformers Without Pre-Training Dependencies.-Closing the Sim-to-Real Gap: Enhancing Autonomous Precision Landing of UAVs with Detection-Informed Deep Reinforcement Learning.- Mitigating Class Imbalance in Healthcare AI Image Classification: Evaluating the Efficacy of Existing Generative Adversarial Network.- More than Noise: Assessing the Viscosity of Food Products Based on Sound Emission.- Vector Analysis of Deep Neural Network Training Process.- Secure Coalition Formation for Federated Machine Learning.- Action Conditioned Attention Encoder-Decoder and Discriminator for Human Motion Generation.- Citation Polarity Identification in Scientific Research Articles Using Deep Learning Methods.- Exploring Physiology-Based Classification of Flow During Musical
Improvisation in Mixed Reality.- Refining Weights for Enhanced Object Similarity in Multi-Perspective 6D of Pose Estimation and 3D Object Detection.- End-to-End Video Surveillance Framework for Anomaly Detection and
Person Re-Identification.- Few-Shot Learning with Novelty Detection.
Learning: Performance Comparison Between N-Gram and TF-IDF.- Evolving Deep Architectures: A New Blend of CNNs and Transformers Without Pre-Training Dependencies.-Closing the Sim-to-Real Gap: Enhancing Autonomous Precision Landing of UAVs with Detection-Informed Deep Reinforcement Learning.- Mitigating Class Imbalance in Healthcare AI Image Classification: Evaluating the Efficacy of Existing Generative Adversarial Network.- More than Noise: Assessing the Viscosity of Food Products Based on Sound Emission.- Vector Analysis of Deep Neural Network Training Process.- Secure Coalition Formation for Federated Machine Learning.- Action Conditioned Attention Encoder-Decoder and Discriminator for Human Motion Generation.- Citation Polarity Identification in Scientific Research Articles Using Deep Learning Methods.- Exploring Physiology-Based Classification of Flow During Musical
Improvisation in Mixed Reality.- Refining Weights for Enhanced Object Similarity in Multi-Perspective 6D of Pose Estimation and 3D Object Detection.- End-to-End Video Surveillance Framework for Anomaly Detection and
Person Re-Identification.- Few-Shot Learning with Novelty Detection.