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Earth Observation Satellites : Task Planning and Scheduling / / by Hao Chen, Shuang Peng, Chun Du, Jun Li
Earth Observation Satellites : Task Planning and Scheduling / / by Hao Chen, Shuang Peng, Chun Du, Jun Li
Autore Chen Hao
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (xii, 189 pages) : illustrations (chiefly color)
Disciplina 629.46
Altri autori (Persone) PengShuang
DuChun
LiJun
Soggetto topico Astronomy
Aerospace engineering
Astronautics
Measurement
Measuring instruments
Solid state physics
Astronomy, Observations and Techniques
Aerospace Technology and Astronautics
Measurement Science and Instrumentation
Electronic Devices
ISBN 9789819935659
9819935652
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Introduction -- 2. Problem description and analysis of EOS task scheduling -- 3. Model and method of ground centralized EOS task scheduling -- 4. EOS Task rescheduling for dynamic factors -- 5. Model and method of ground distributed EOS task scheduling -- 6. Model and method of EOS onboard autonomous task scheduling -- 7. Satellite task scheduling system -- 8. Summary and prospect.
Record Nr. UNINA-9910743681203321
Chen Hao  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Trustworthy Machine Learning for Healthcare [[electronic resource] ] : First International Workshop, TML4H 2023, Virtual Event, May 4, 2023, Proceedings / / edited by Hao Chen, Luyang Luo
Trustworthy Machine Learning for Healthcare [[electronic resource] ] : First International Workshop, TML4H 2023, Virtual Event, May 4, 2023, Proceedings / / edited by Hao Chen, Luyang Luo
Autore Chen Hao
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (207 pages)
Disciplina 006.31
Altri autori (Persone) LuoLuyang
Collana Lecture Notes in Computer Science
Soggetto topico Machine learning
Machine Learning
ISBN 3-031-39539-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Do Tissue Source Sites leave identifiable Signatures in Whole Slide Images beyond staining? -- Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography -- Privacy-preserving machine learning for healthcare: open challenges and future perspectives -- Self-Supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-grained Time Resolution. Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants. Isabel Chien, Javier Gonzalez Hernandez, Richard E Turner -- CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs -- ExBEHRT: Extended Transformer for Electronic Health Records -- Stasis: Reinforcement Learning Simulators for Human-Centric Real-World Environments. Cross-domain Microscopy Cell Counting by Disentangled Transfer Learning -- Post-hoc Saliency Methods Fail to Capture Latent Feature Importance in Time Series Data -- Enhancing Healthcare Model Trustworthiness through Theoretically Guaranteed One-Hidden-Layer CNN Purification -- A Kernel Density Estimation based Quality Metric for Quality Assessment of Obstetric Ultrasound Video -- Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth -- Conformal Prediction Masks: Visualizing Uncertainty in Medical Imaging -- Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness -- Geometry-Based end-to-end Segmentation of Coronary artery ib Computed Tomography Angiograph.
Record Nr. UNISA-996542665303316
Chen Hao  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Trustworthy Machine Learning for Healthcare : First International Workshop, TML4H 2023, Virtual Event, May 4, 2023, Proceedings / / edited by Hao Chen, Luyang Luo
Trustworthy Machine Learning for Healthcare : First International Workshop, TML4H 2023, Virtual Event, May 4, 2023, Proceedings / / edited by Hao Chen, Luyang Luo
Autore Chen Hao
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (207 pages)
Disciplina 006.31
Altri autori (Persone) LuoLuyang
Collana Lecture Notes in Computer Science
Soggetto topico Machine learning
Machine Learning
ISBN 9783031395390
3031395395
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Do Tissue Source Sites leave identifiable Signatures in Whole Slide Images beyond staining? -- Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography -- Privacy-preserving machine learning for healthcare: open challenges and future perspectives -- Self-Supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-grained Time Resolution. Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants. Isabel Chien, Javier Gonzalez Hernandez, Richard E Turner -- CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs -- ExBEHRT: Extended Transformer for Electronic Health Records -- Stasis: Reinforcement Learning Simulators for Human-Centric Real-World Environments. Cross-domain Microscopy Cell Counting by Disentangled Transfer Learning -- Post-hoc Saliency Methods Fail to Capture Latent Feature Importance in Time Series Data -- Enhancing Healthcare Model Trustworthiness through Theoretically Guaranteed One-Hidden-Layer CNN Purification -- A Kernel Density Estimation based Quality Metric for Quality Assessment of Obstetric Ultrasound Video -- Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth -- Conformal Prediction Masks: Visualizing Uncertainty in Medical Imaging -- Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness -- Geometry-Based end-to-end Segmentation of Coronary artery ib Computed Tomography Angiograph.
Record Nr. UNINA-9910736014203321
Chen Hao  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui