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期刊列表
Pattern Recognition
Volume 121
Pattern Recognition
(PR)
-
Volume 121
论文列表
点击这里查看 Pattern Recognition 的JCR分区、影响因子等信息
卷期号:
Volume 121
发布时间:
January 2022
卷期年份:
2022
卷期官网:
https://www.sciencedirect.com/journal/pattern-recognition/vol/121/suppl/C
本期论文列表
Editorial Board
原文链接
谷歌学术
必应学术
百度学术
Delving deep into spatial pooling for squeeze-and-excitation networks
原文链接
谷歌学术
必应学术
百度学术
Lifelong robotic visual-tactile perception learning
原文链接
谷歌学术
必应学术
百度学术
Indefinite twin support vector machine with DC functions programming
原文链接
谷歌学术
必应学术
百度学术
Unified learning approach for egocentric hand gesture recognition and fingertip detection
原文链接
谷歌学术
必应学术
百度学术
Graph variational auto-encoder for deriving EEG-based graph embedding
原文链接
谷歌学术
必应学术
百度学术
Semi-supervised student-teacher learning for single image super-resolution
原文链接
谷歌学术
必应学术
百度学术
Creating synthetic minority class samples based on autoencoder extreme learning machine
原文链接
谷歌学术
必应学术
百度学术
WC-KNNG-PC: Watershed clustering based on k-nearest-neighbor graph and Pauta Criterion
原文链接
谷歌学术
必应学术
百度学术
Tracking more than 100 arbitrary objects at 25 FPS through deep learning
原文链接
谷歌学术
必应学术
百度学术
Novel fuzzy clustering algorithm with variable multi-pixel fitting spatial information for image segmentation
原文链接
谷歌学术
必应学术
百度学术
ANCES: A novel method to repair attribute noise in classification problems
原文链接
谷歌学术
必应学术
百度学术
4D computed tomography super-resolution reconstruction based on tensor product and nuclear norm optimization
原文链接
谷歌学术
必应学术
百度学术
Mixture factor analysis with distance metric constraint for dimensionality reduction
原文链接
谷歌学术
必应学术
百度学术
Relation-aware dynamic attributed graph attention network for stocks recommendation
原文链接
谷歌学术
必应学术
百度学术
Multi-dimensional clustering through fusion of high-order similarities
原文链接
谷歌学术
必应学术
百度学术
Consistent and diverse multi-View subspace clustering with structure constraint
原文链接
谷歌学术
必应学术
百度学术
Action recognition via pose-based graph convolutional networks with intermediate dense supervision
原文链接
谷歌学术
必应学术
百度学术
SAR-to-optical image translation based on improved CGAN
原文链接
谷歌学术
必应学术
百度学术
Object-based cluster validation with densities
原文链接
谷歌学术
必应学术
百度学术
Blitz-SLAM: A semantic SLAM in dynamic environments
原文链接
谷歌学术
必应学术
百度学术
Variable weight algorithm for convolutional neural networks and its applications to classification of seizure phases and types
原文链接
谷歌学术
必应学术
百度学术
The residual generator: An improved divergence minimization framework for GAN
原文链接
谷歌学术
必应学术
百度学术
Spatiotemporal consistency-enhanced network for video anomaly detection
原文链接
谷歌学术
必应学术
百度学术
Head pose estimation using deep neural networks and 3D point clouds
原文链接
谷歌学术
必应学术
百度学术
Learning discriminative region representation for person retrieval
原文链接
谷歌学术
必应学术
百度学术
Towards robust explanations for deep neural networks
原文链接
谷歌学术
必应学术
百度学术
Learning hybrid ranking representation for person re-identification
原文链接
谷歌学术
必应学术
百度学术
Deep neural networks-based relevant latent representation learning for hyperspectral image classification
原文链接
谷歌学术
必应学术
百度学术
Pedestrian attribute recognition: A survey
原文链接
谷歌学术
必应学术
百度学术
Why is this an anomaly? Explaining anomalies using sequential explanations
原文链接
谷歌学术
必应学术
百度学术
Graph convolutional autoencoders with co-learning of graph structure and node attributes
原文链接
谷歌学术
必应学术
百度学术
Part-based annotation-free fine-grained classification of images of retail products
原文链接
谷歌学术
必应学术
百度学术
Pedestrian trajectory prediction with convolutional neural networks
原文链接
谷歌学术
必应学术
百度学术
A hierarchical model for learning to understand head gesture videos
原文链接
谷歌学术
必应学术
百度学术
Universal multi-Source domain adaptation for image classification
原文链接
谷歌学术
必应学术
百度学术
Preference prediction based on a photo gallery analysis with scene recognition and object detection
原文链接
谷歌学术
必应学术
百度学术
Deep anomaly detection with self-supervised learning and adversarial training
原文链接
谷歌学术
必应学术
百度学术
A novel GCN-based point cloud classification model robust to pose variances
原文链接
谷歌学术
必应学术
百度学术
Deep tree-ensembles for multi-output prediction
原文链接
谷歌学术
必应学术
百度学术
Learning common and label-specific features for multi-Label classification with correlation information
原文链接
谷歌学术
必应学术
百度学术
Towards open-set touchless palmprint recognition via weight-based meta metric learning
原文链接
谷歌学术
必应学术
百度学术
Learning scale awareness in keypoint extraction and description
原文链接
谷歌学术
必应学术
百度学术
Learning sequentially diversified representations for fine-grained categorization
原文链接
谷歌学术
必应学术
百度学术
Constrained mutual convex cone method for image set based recognition
原文链接
谷歌学术
必应学术
百度学术
Recursive multi-model complementary deep fusion for robust salient object detection via parallel sub-networks
原文链接
谷歌学术
必应学术
百度学术
BiconNet: An edge-preserved connectivity-based approach for salient object detection
原文链接
谷歌学术
必应学术
百度学术
Context-aware co-supervision for accurate object detection
原文链接
谷歌学术
必应学术
百度学术
Joint multi-label learning and feature extraction for temporal link prediction
原文链接
谷歌学术
必应学术
百度学术
Edge computing enabled video segmentation for real-time traffic monitoring in internet of vehicles
原文链接
谷歌学术
必应学术
百度学术
Transtrack: Online meta-transfer learning and Otsu segmentation enabled wireless gesture tracking
原文链接
谷歌学术
必应学术
百度学术
Cloud based scalable object recognition from video streams using orientation fusion and convolutional neural networks
原文链接
谷歌学术
必应学术
百度学术
A Unified Hierarchical XGBoost model for classifying priorities for COVID-19 vaccination campaign
原文链接
谷歌学术
必应学术
百度学术
Pareto optimization of deep networks for COVID-19 diagnosis from chest X-rays
原文链接
谷歌学术
必应学术
百度学术
Online aggregation of probability forecasts with confidence
原文链接
谷歌学术
必应学术
百度学术
GLMNet: Graph learning-matching convolutional networks for feature matching
原文链接
谷歌学术
必应学术
百度学术
Learning to schedule multi-NUMA virtual machines via reinforcement learning
原文链接
谷歌学术
必应学术
百度学术
Estimating fund-raising performance for start-up projects from a market graph perspective
原文链接
谷歌学术
必应学术
百度学术
Financial time series forecasting with multi-modality graph neural network
原文链接
谷歌学术
必应学术
百度学术
Expression of concern: “What-and-where to match: Deep spatially multiplicative integration networks for person re-identification” [Pattern Recognition, Volume 76, April 2018, Pages 727-738]
原文链接
谷歌学术
必应学术
百度学术
Expression of concern: “Deep Adaptive Feature Embedding with Local Sample Distributions for Person Re-identification” [Pattern Recognition, Volume 73, January 2018, Pages 275-288]
原文链接
谷歌学术
必应学术
百度学术