Pattern Recognition and Computer Vision
Springer International Publishing (Verlag)
978-3-031-18909-8 (ISBN)
The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking.
Biomedical Image Processing and Analysis.- ED-AnoNet: Elastic Distortion-Based Unsupervised Network for OCT Image Anomaly Detection.- BiDFNet: Bi-decoder and Feedback Network for Automatic Polyp Segmentation with Vision Transformers.- FundusGAN: A One-Stage Single Input GAN for Fundus Synthesis.- DIT-NET: Joint Deformable Network and Intra-class Transfer GAN for cross-domain 3D Neonatal Brain MRI segmentation.- Classification of sMRI Images for Alzheimer's Disease by Using Neural Networks.- Semi-Supervised Distillation Learning Based on Swin Transformer for MRI Reconstruction.- Multi-Scale Multi-Target Domain Adaptation for Angle Closure Classification.- Automatic glottis segmentation method based on lightweight U-net.- Decouple U-Net: A Method for the Segmentation and Counting of Macrophages in Whole Slide Imaging.- A Zero-training Method for RSVP-based Brain Computer Interface.- An improved tensor network for image classification in histopathology.- DeepEnReg: Joint Enhancement and Ane Registration for Low-contrast Medical Images.- Fluorescence Microscopy Images Segmentation based on Prototypical Networks with a few Annotations.- SuperVessel: Segmenting High-resolution Vessel from Low-resolution Retinal Image.- Cascade Multiscale Swin-Conv Network for Fast MRI Reconstruction.- DEST: Deep Enhanced Swin Transformer toward Better Scoring for NAFLD.- CTCNet: A Bi-directional Cascaded Segmentation Network Combining Transformers with CNNs for Skin Lesions.- MR Image Denoising Based On Improved Multipath Matching Pursuit Algorithm.- Statistical characteristics of 3-D PET imaging: a comparison between conventional and total-body PET scanners.- Unsupervised medical image registration based on multi-scale cascade network.- A Novel Local-global Spatial Attention Network for Cortical Cataract Classification in AS-OCT.- PRGAN:A Progressive Refined GAN for Lesion Localization and Segmentation on High-Resolution Retinal fundus Photography.- Multiscale Autoencoder with Structural-Functional Attention Network for Alzheimer's Disease Prediction.- Robust Liver Segmentation Using Boundary Preserving Dual Attention Network.- msFormer: Adaptive Multi-Modality 3D Transformer for Medical Image Segmentation.- Semi-supervised Medical Image Segmentation with Semantic Distance Distribution Consistency Learning.- MultiGAN: multi-domain image translation from OCT to OCTA_ TransPND: A Transformer based Pulmonary Nodule Diagnosis Method on CT Image.- Adversarial Learning Based Structural Brain-network Generative Model for Analyzing Mild Cognitive Impairment.- A 2.5D Coarse-to-fine Framework for 3D Cardiac CT View Planning.- Weakly Supervised Semantic Segmentation of Echocardiography Videosvia Multi-level Features Selection.- DPformer: Dual-path transformers forgeometric and appearancefeatures reasoning in diabetic retinopathy grading.- Deep Supervoxel Mapping Learning for Dense Correspondence of Cone-Beam Computed Tomography.- Manifold-Driven and Feature Replay Lifelong Representation Learning on Person ReID.- Multi-source information-shared domain adaptation for EEG emotion recognition.- Spatial-Channel Mixed Attention based Network for Remote Heart Rate Estimation.- Weighted Graph Based Feature Representation for Finger-Vein Recognition.- Self-Supervised Face Anti-Spoofng via Anti-Contrastive Learning.- Counterfactual Image Enhancement for Explanation of Face Swap Deepfakes.- Improving Pre-trained Masked Autoencoder with Locality Enhancement for Person Re-identification.- MINIPI : a MultI-scale Neural network based impulse radio ultra-wideband radar Indoor Personnel Identification method.- PSU-Net: Paired Spatial U-Net for hand segmentation with complex backgrounds.- Pattern Classification and Clustering.- Human Knowledge-Guided and Task-Augmented Deep Learning for Glioma Grading.- Learning to Cluster Faces with Mixed Face Quality.- Capturing Prior Knowledge in Soft Labels for Classification with Limited or Imbalanced Data.- Coupled Learning for Kernel Representation and Graph Tensor in Multi-view Subspace Clustering.- Combating Noisy Labels via Contrastive Learning with Challenging Pairs.- Semantic Center Guided Windows Attention Fusion Framework for Food Recognition.- Adversarial Bidirectional Feature Generation for Generalized Zero-Shot Learning under Unreliable Semantics.- Exploiting Robust Memory Features for Unsupervised Reidentification.- TIR: A Two-stage Insect Recognition method for convolutional neural network.- Discerning Coteaching: A Deep Framework for Automatic Identification of Noise Labels.- VDSSA: Ventral & Dorsal Sequential Self-attention AutoEncoder for Cognitive-Consistency Disentanglement.- Bayesian Neural Networks with Covariate Shift Correction for Classification in -ray Astrophysics.
| Erscheinungsdatum | 14.10.2022 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XVIII, 723 p. 264 illus., 237 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1122 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Applications • Artificial Intelligence • Bioinformatics • Computer Networks • Computer Science • computer vision • conference proceedings • Deep learning • Image Analysis • image matching • Image Processing • Image Quality • image reconstruction • Image Segmentation • Imaging Systems • Informatics • machine learning • Medical Images • Neural networks • Object recognition • pattern recognition • Research • Signal Processing |
| ISBN-10 | 3-031-18909-4 / 3031189094 |
| ISBN-13 | 978-3-031-18909-8 / 9783031189098 |
| Zustand | Neuware |
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