Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
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
|
||
| Basel : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Human Activity Recognition and Anomaly Detection : 4th International Workshop, DL-HAR 2024, and First International Workshop, ADFM 2024, Held in Conjunction with IJCAI 2024, Jeju, South Korea, August 3–9, 2024, Revised Selected Papers / / edited by Kuan-Chuan Peng, Yizhou Wang, Ziyue Li, Zhenghua Chen, Jianfei Yang, Sungho Suh, Min Wu
| Human Activity Recognition and Anomaly Detection : 4th International Workshop, DL-HAR 2024, and First International Workshop, ADFM 2024, Held in Conjunction with IJCAI 2024, Jeju, South Korea, August 3–9, 2024, Revised Selected Papers / / edited by Kuan-Chuan Peng, Yizhou Wang, Ziyue Li, Zhenghua Chen, Jianfei Yang, Sungho Suh, Min Wu |
| Autore | Peng Kuan-Chuan |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (156 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
WangYizhou
LiZiyue ChenZhenghua YangJianfei SuhSungho WuMin |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Artificial intelligence
Compilers (Computer programs) Computer simulation Artificial Intelligence Compilers and Interpreters Computer Modelling |
| ISBN |
9789819790036
9789819790029 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Anomaly Detection with Foundation Models. -- GPT-4V-AD: Exploring Grounding Potential of VQA-oriented GPT-4V for Zero-shot Anomaly Detection. -- CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection. -- DDPM-MoCo: Advancing Industrial Surface Defect Generation and Detection with Generative and Contrastive Learning. -- Dual Memory-guided Probabilistic Model for Weakly-supervised Anomaly Detection. -- Deep Learning for Human Activity Recognition. -- Real-Time Human Action Prediction via Pose Kinematics. -- Uncertainty Awareness for Unsupervised Domain Adaptation on Human Activity Recognition. -- Deep Interaction Feature Fusion for Robust Human Activity Recognition. -- How effective are Self-Supervised models for Contact Identification in Videos. -- A Wearable Multi-Modal Edge-Computing System for Real-Time Kitchen Activity Recognition. |
| Record Nr. | UNINA-9910983029903321 |
|
Peng Kuan-Chuan
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||