Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.05.2025

Abbildungen

LV, 151 illus., 145 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Alessio Del Bue + weitere

Verlag

Springer

Seitenzahl

420

Maße (L/B/H)

23,5/15,5/2,6 cm

Gewicht

715 g

Sprache

Englisch

ISBN

978-3-031-91906-0

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.05.2025

Abbildungen

LV, 151 illus., 145 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Verlag

Springer

Seitenzahl

420

Maße (L/B/H)

23,5/15,5/2,6 cm

Gewicht

715 g

Sprache

Englisch

ISBN

978-3-031-91906-0

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: GPSR Kontakt

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)

  • Produktbild: Computer Vision – ECCV 2024 Workshops
  • .- TONO: a synthetic dataset for face image compliance to ISO/ICAO standard.

    .- mproving Post-Earthquake Crack Detection using Semi-Synthetic Gener ated Images.

    .- DiffAugment: Diffusion based Long-Tailed Visual Relationship Recognition.

    .- Neural Transcoding Vision Transformers for EEG-to-fMRI Synthesis.

    .- RoCOCO: Robustness Benchmark of MS-COCO to Stress-test Image-Text Matching Models.

    .- NeRFmentation: NeRF-based Augmentation for Monocular Depth Estima tion.

    .- Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition.

    .- Time-Resolved MNIST Dataset for Single-Photon Recognition.

    .- NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Hu man Pose Estimation in Top-View Fisheye Images.

    .- Training and Benchmarking Leukocyte Sub-types Classification Methods with Synthetic Images.

    .- DALDA: Data Augmentation Leveraging Diffusion Model and LLM with Adaptive Guidance Scaling.

    .- Contextual Knowledge Pursuit for Faithful Visual Synthesis.

    .- SurgicaL-CD: Generating Surgical Images via Unpaired Image Translation with Latent Consistency Diffusion Models.

    .- Diffusion-based Synthetic Dataset Generation for Egocentric 3D Human Pose Estimation.

    .- BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabil ities in Pretrained Diffusion Models.

    .- A CycleGAN Model to Synthesize Missing and Unpaired MRI Sequences for Under-Represented Multiple Sclerosis Lesions.

    .- The Impact of Balancing Real and Synthetic Data on Accuracy and Fairness in Face Recognition.

    .- DreamTexture: High-Fidelity Synthetic 3D Data Generation through De coupled Geometry and Texture Synthesis.

    .- Control+Shift: Generating Controllable Distribution Shifts.

    .- Comparative Analysis of Synthetic and Real Melanoma Images in AI-Driven Diagnosis.

    .- How Knowledge Distillation Mitigates the Synthetic Gap in Fair Face Recog nition.

    .- Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization.

    .- FABRIC: Personalizing Diffusion Models with Iterative Feedback.

    .- TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection.