Description

Book Synopsis

.- On the Application of Egocentric Computer Vision to Industrial Inspection.
.- NeuroSymbolic Visual Transform based on Logic Tensor Network for Defect Detection.
.- Multimodal computer vision techniques for wooden utility pole density esti mation with contact-free sensing.
.- Dynamic Label Injection for Imbalanced Industrial Defect Segmentation.
.- XAI-guided Insulator Anomaly Detection for Imbalanced Datasets.
.- Exploring Multi-modal Neural Scene Representations With Applications on Thermal Imaging.
.- Foreground-Aware Knowledge Distillation for Enhanced Damage Detection.
.- AnomalyFactory: Regard Anomaly Generation as Unsupervised Anomaly Localization.
.- Interactive Explainable Anomaly Detection for Industrial Settings.
.- DAS3D: Dual-modality Anomaly Synthesis for 3D Anomaly Detection.
.- SQUAD: Scalar Quantized representation learning for Unsupervised Anomaly Detection and localization.
.- Deep Unsupervised Segmentation of Log Point Clouds.
.- A Computer Vision System for Automatic Edge Detection of Magnetic Grain Profile.
.- Find the Assembly Mistakes: Error Segmentation for Industrial Applications.
.- EM Based Nano-Scale Defect Analysis in Semiconductor Man ufacturing for Advanced IC Nodes.
.- On The Relationship between Visual Anomaly-free and Anomalous Representations.
.- DIE-VIS: an Automated Visual Inspection System for Cardboard Box Manufacturing.
.- When the Small-Loss Trick is Not Enough: Multi-Label Image Classification with Noisy Labels Applied to CCTV Sewer Inspections.
.- AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection.
.- Self-supervised Models are Strong Industrial Few-shot Classification Learners.
.- Hyperspectral Imaging and Computer Vision Based Remote Monitoring of SO2 Emissions in Maritime Vessels.
.- Temporal-consistent CAMs for Weakly Supervised Video Segmentation in Waste Sorting.
.- Sequential PatchCore: Anomaly Detection for Surface Inspection using Synthetic Impurities.
.- SplatPose+: Real Time Image-Based Pose-Agnostic 3D Anomaly Detection.
.- BBD-Polyp: Weakly Supervised Polyp Segmentation via Bounding Box and
Depth Map.
.- ENSTRECT: A Stage-based Approach to 2.5D Structural Damage Detection.
.- An Augmentation-based Model Re-adaptation Framework for Robust Image Segmentation.
.- Meta Learning-Driven Iterative Refinement for Robust Anomaly Detection in Industrial Inspection.

Computer Vision ECCV 2024 Workshops

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    A Paperback by Alessio Del Bue

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      View other formats and editions of Computer Vision ECCV 2024 Workshops by Alessio Del Bue

      Publisher: Springer
      Publication Date: 23/05/2025
      ISBN13: 9783031928048, 978-3031928048
      ISBN10:
      Also in:
      Computing Image processing

      Description

      Book Synopsis

      .- On the Application of Egocentric Computer Vision to Industrial Inspection.
      .- NeuroSymbolic Visual Transform based on Logic Tensor Network for Defect Detection.
      .- Multimodal computer vision techniques for wooden utility pole density esti mation with contact-free sensing.
      .- Dynamic Label Injection for Imbalanced Industrial Defect Segmentation.
      .- XAI-guided Insulator Anomaly Detection for Imbalanced Datasets.
      .- Exploring Multi-modal Neural Scene Representations With Applications on Thermal Imaging.
      .- Foreground-Aware Knowledge Distillation for Enhanced Damage Detection.
      .- AnomalyFactory: Regard Anomaly Generation as Unsupervised Anomaly Localization.
      .- Interactive Explainable Anomaly Detection for Industrial Settings.
      .- DAS3D: Dual-modality Anomaly Synthesis for 3D Anomaly Detection.
      .- SQUAD: Scalar Quantized representation learning for Unsupervised Anomaly Detection and localization.
      .- Deep Unsupervised Segmentation of Log Point Clouds.
      .- A Computer Vision System for Automatic Edge Detection of Magnetic Grain Profile.
      .- Find the Assembly Mistakes: Error Segmentation for Industrial Applications.
      .- EM Based Nano-Scale Defect Analysis in Semiconductor Man ufacturing for Advanced IC Nodes.
      .- On The Relationship between Visual Anomaly-free and Anomalous Representations.
      .- DIE-VIS: an Automated Visual Inspection System for Cardboard Box Manufacturing.
      .- When the Small-Loss Trick is Not Enough: Multi-Label Image Classification with Noisy Labels Applied to CCTV Sewer Inspections.
      .- AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection.
      .- Self-supervised Models are Strong Industrial Few-shot Classification Learners.
      .- Hyperspectral Imaging and Computer Vision Based Remote Monitoring of SO2 Emissions in Maritime Vessels.
      .- Temporal-consistent CAMs for Weakly Supervised Video Segmentation in Waste Sorting.
      .- Sequential PatchCore: Anomaly Detection for Surface Inspection using Synthetic Impurities.
      .- SplatPose+: Real Time Image-Based Pose-Agnostic 3D Anomaly Detection.
      .- BBD-Polyp: Weakly Supervised Polyp Segmentation via Bounding Box and
      Depth Map.
      .- ENSTRECT: A Stage-based Approach to 2.5D Structural Damage Detection.
      .- An Augmentation-based Model Re-adaptation Framework for Robust Image Segmentation.
      .- Meta Learning-Driven Iterative Refinement for Robust Anomaly Detection in Industrial Inspection.

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