Hieronymi Bagolini In interpretationem Alexandri Aphrodisei De fato praefatio ... Alexandri Aphrodisei Liber unicus De fato & libero arbitrio ... Hieronymo Bagolino interprete. Eiusdem Hieronymi in interpretationem Alexandri Aphrodisei de intellectu ... paraefatio. Alexandri Aphrodisei libellus de intellectu, oedem interprete. Eiusdem Hieronymi praefatio ad lectores. Alexandri Aphrodisei ex libris questionum naturalium capita tria de fato, de eo quod in nobis est, de prouidentia, eodem interprete [[electronic resource]]

• Record Nr.: UNINA9910481190803321
• Autore: Alexander of Aphrodisias
• Pubbl/distr/stampa: Italy, : [s.n.], 1516
• Descrizione fisica: Online resource ([56] c., 4)
• Lingua di pubblicazione: Latino
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Reproduction of original in Biblioteca Nazionale Centrale di Firenze.

Flow measurement engineering handbook / R.W. Miller

• Record Nr.: UNICASRML0308854
• Autore: Miller, Richard W.
• Pubbl/distr/stampa: New York, : McGraw-Hill, c1989
• ISBN: 0070420467
• Edizione: [2. ed]
• Descrizione fisica: XL, 1033 p. in varie sequenze ; 24 cm.
• Disciplina: 681.2
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part V / / edited by Biao Luo, Long Cheng, Zheng-Guang Wu, Hongyi Li, Chaojie Li

• Record Nr.: UNINA9910763598503321
• Pubbl/distr/stampa: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
• ISBN: 981-9980-73-9
• Edizione: [1st ed. 2024.]
• Descrizione fisica: 1 online resource (620 pages)
• Collana: Lecture Notes in Computer Science, , 1611-3349 ; ; 14451
• Disciplina: 006.3
• Soggetti: Pattern recognition systems; Data mining; Machine learning; Social sciences - Data processing; Automated Pattern Recognition; Data Mining and Knowledge Discovery; Machine Learning; Computer Application in Social and Behavioral Sciences
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Text to Image Generation with Conformer-GAN -- MGFNet: A Multi-Granularity Feature Fusion and Mining Network for Visible-Infrared Person Re-Identification -- Isomorphic Dual-Branch Network for Non-homogeneous Image Dehazing and Super-Resolution -- Hi-Stega : A Hierarchical Linguistic Steganography Framework Combining Retrieval and Generation -- Effi-Seg: Rethinking EfficientNet Architecture for Real-time Semantic Segmentation -- Quantum Autoencoder Frameworks for Network Anomaly Detection -- Spatially-Aware Human-Object Interaction Detection with Cross-Modal Enhancement -- Intelligent trajectory tracking control of unmanned parafoil system based on SAC optimized LADRC -- CATS: Connection-aware and Interaction-based Text Steganalysis in Social Networks -- Syntax Tree Constrained Graph Network for Visual Question Answering -- CKR-Calibrator: Convolution Kernel Robustness Evaluation and Calibration -- SGLP-Net: Sparse Graph Label Propagation Network for Weakly-Supervised Temporal Action Localization -- VFIQ: A Novel Model of ViT-FSIMc Hybrid Siamese Network for Image Quality Assessment -- Spiking Reinforcement Learning for Weakly-supervised Anomaly Detection -- Resource-aware DNN Partitioning for Privacy-sensitive Edge-Cloud Systems -- A frequency reconfigurable multi-mode printed antenna -- Multi-view Contrastive learning for Knowledge-aware Recommendation -- PYGC: a PinYin Language Model Guided Correction Model for Chinese Spell Checking -- Empirical Analysis of Multi-label Classification on GitterCom using BERT -- A lightweight safety helmet detection network based on bidirectional connection module and Polarized Self-Attention -- Direct Inter-Intra View Association for Light Field Super-Resolution -- Responsive CPG-Based Locomotion Control for Quadruped Robots -- Vessel Behavior Anomaly Detection using Graph Attention Network -- TASFormer: Task-aware Image Segmentation Transformer -- Unsupervised Joint-Semantics Autoencoder Hashing for Multimedia Retrieval -- TKGR-RHETNE：A New Temporal Knowledge Graph Reasoning Model via Jointly Modeling Relevant Historical Event and Temporal Neighborhood Event Context -- High-Resolution Self-Attention with Fair Loss for Point Cloud Segmentation -- Transformer-based Video Deinterlacing Method -- SCME: A Self-Contrastive Method for Data-free and Query-Limited Model Extraction Attack -- CSEC: A Chinese Semantic Error Correction Dataset for Written Correction -- Contrastive Kernel Subspace Clustering -- UATR: An Uncertainty Aware Two-stage Refinement Model for Targeted Sentiment Analysis -- AttIN: Paying More Attention to Neighborhood Information for Entity Typing in Knowledge Graphs -- Text-based Person Re-ID by Saliency Mask and Dynamic Label Smoothing -- Robust Multi-view Spectral Clustering with Auto-encoder for Preserving Information -- Learnable Color Image Zero-Watermarking Based on Feature Comparison -- P-IoU: Accurate Motion Prediction based Data Association for Multi-Object Tracking -- WCA-VFnet:a dedicated complex forest smoke fire detector -- Label Selection Algorithm Based on Ant Colony Optimization and Reinforcement Learning for Multi-label Classification -- Reversible Data Hiding Based on Adaptive Embedding with Local Complexity -- Generalized Category Discovery with Clustering Assignment Consistency -- CInvISP: Conditional Invertible Image Signal Processing Pipeline -- Ignored Details in Eyes: Exposing GAN-generated Faces by Sclera -- A Developer Recommendation Method Based on Disentangled ; -- Graph Convolutional Network -- Novel Method for Radar Echo Target Detection.
• Sommario/riassunto: The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. .