Pattern Recognition and Computer Vision

Pattern Recognition and Computer Vision

5th Chinese Conference, PRCV 2022, Shenzhen, China, November 4-7, 2022, Proceedings, Part II

Lai, Jianhuang; Han, Junwei; Yuen, Pong C.; Zhang, Zhaoxiang; Tan, Tieniu; Guo, Yike; Zhang, Jianguo; Yu, Shiqi

Springer International Publishing AG

10/2022

723

Mole

Inglês

9783031189098

15 a 20 dias

Descrição não disponível.
?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.
artificial intelligence;bioinformatics;computer networks;computer vision;deep learning;image analysis;image matching;image processing;image quality;image reconstruction;image segmentation;imaging systems;machine learning;medical images;neural networks;object recognition;pattern recognition;signal processing