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AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD) / / Kuan-Chuan Peng, Ziyan Wu
| AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD) / / Kuan-Chuan Peng, Ziyan Wu |
| Autore | Peng Kuan-Chuan |
| Pubbl/distr/stampa | Basel : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2022 |
| Descrizione fisica | 1 electronic resource (186 p.) |
| Disciplina | 006.3 |
| Soggetto topico |
Technology: general issues
Artificial intelligence History of engineering & technology |
| Soggetto non controllato |
permutation equivariance
optimization gender bias fairness face-recognition models facial attributes social bias bias detection natural language processing temporal bias forecasting contrastive learning supervised contrastive learning transfer learning robustness noisy labels coresets deep learning contextualized embeddings out-of-distribution generalization |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | About the Editors -- Statement of Peer Review -- Electricity Consumption Forecasting for Out-of-Distribution Time-of-Use Tariffs -- Measuring Embedded Human-Like Biases in Face Recognition Models -- Measuring Gender Bias in Contextualized Embeddings -- The Details Matter: Preventing Class Collapsein Supervised Contrastive Learning -- DAP-SDD: Distribution-Aware Pseudo Labeling for Small Defect Detection -- Quantifying Bias in a Face -- Verification System -- Super-Resolution for Brain MR Images from a Significantly Small Amount of Training Data -- Dual Complementary Prototype Learning for Few-Shot Segmentation -- Extracting Salient Facts from Company Reviews with Scarce Labels -- Long-Tail Zero and Few-Shot Learning via Contrastive Pretraining on and for Small Data -- Age Should Not Matter: -- Towards More Accurate Pedestrian Detection via Self-Training. |
| Altri titoli varianti | AAAI Workshop on Artificial Intelligence with Biased or Scarce Data |
| Record Nr. | UNINA-9910585937403321 |
Peng Kuan-Chuan
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| Basel : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements
| Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements |
| Autore | Das Monidipa |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (112 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
scene classification
teacher-student noisy labels knowledge distillation remote sensing images LightGBM spatiotemporal weight interpolation AOD recovery East Asia polarized SAR optical image random forest conditional random fields feature-level fusion Dirichlet process infinite mixture models Gamma distribution variational inference online setting oil spill detection synthetic aperture radar images GNSS-R CYGNSS high wind speed inversion SVR PCA-SVR CNN |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910585940903321 |
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Das Monidipa
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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