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Explainable and Interpretable Models in Computer Vision and Machine Learning / / edited by Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven
| Explainable and Interpretable Models in Computer Vision and Machine Learning / / edited by Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (305 pages) |
| Disciplina | 006.31 |
| Collana | The Springer Series on Challenges in Machine Learning |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Artificial Intelligence Image Processing and Computer Vision Pattern Recognition |
| ISBN | 3-319-98131-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Considerations for Evaluation and Generalization in Interpretable Machine Learning -- 2 Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges -- 3 Learning Functional Causal Models with Generative Neural Networks -- 4 Learning Interpretable Rules for Multi-label Classification -- 5 Structuring Neural Networks for More Explainable Predictions -- 6 Generating Post-Hoc Rationales of Deep Visual Classification Decisions -- 7 Ensembling Visual Explanations -- 8 Explainable Deep Driving by Visualizing Causal Action -- 9 Psychology Meets Machine Learning: Interdisciplinary Perspectives on Algorithmic Job Candidate Screening -- 10 Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions -- 11 On the Inherent Explainability of Pattern Theory-based Video Event Interpretations. . |
| Record Nr. | UNINA-9910299353403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Inpainting and Denoising Challenges / / edited by Sergio Escalera, Stephane Ayache, Jun Wan, Meysam Madadi, Umut Güçlü, Xavier Baró
| Inpainting and Denoising Challenges / / edited by Sergio Escalera, Stephane Ayache, Jun Wan, Meysam Madadi, Umut Güçlü, Xavier Baró |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (151 pages) |
| Disciplina | 621.3822 |
| Collana | The Springer Series on Challenges in Machine Learning |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Artificial Intelligence Image Processing and Computer Vision Pattern Recognition |
| ISBN | 3-030-25614-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. A Brief Review of Image Denoising Algorithms and Beyond -- 2. ChaLearn Looking at People: Inpainting and Denoising Challenges -- 3. U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting -- 4. FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks -- 5. Iterative Application of Autoencoders for Video Inpainting and Fingerprint Denoising -- 6. Video DeCaptioning using U-Net with Stacked Dilated Convolutional Layers -- 7. Joint Caption Detection and Inpainting using Generative Network -- 8. Generative Image Inpainting for Person Pose Generation -- 9. Person Inpainting with Generative Adversarial Networks -- 10. Road Layout Understanding by Generative Adversarial Inpainting -- 11. Photo-realistic and Robust Inpainting of Faces using Refinement GANs. |
| Record Nr. | UNINA-9910349272303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||