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h5 指数:80
h5 中位数:138

h5 指数是指在过去整整 5 年中所发表文章的 h 指数。h 指在 2018-2022 年间发表的 h 篇文章每篇至少都被引用过 h 次的最大值。隐藏

出版物的 h5 中位数，是指出版物的 h5 指数所涵盖的所有文章获得的引用次数的中位值。隐藏

#11 Computer Vision & Pattern Recognition

标题/作者	引用次数	年份
Deep learning for sensor-based activity recognition: A survey J Wang, Y Chen, S Hao, X Peng, L Hu Pattern Recognition Letters 119, 3-11	1664	2019
COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images P Afshar, S Heidarian, F Naderkhani, A Oikonomou, KN Plataniotis, ... Pattern Recognition Letters 138, 638-643	597	2020
A novel deep learning based framework for the detection and classification of breast cancer using transfer learning SU Khan, N Islam, Z Jan, IU Din, JJPC Rodrigues Pattern Recognition Letters 125, 1-6	578	2019
A survey of recent advances in CNN-based single image crowd counting and density estimation VA Sindagi, VM Patel Pattern Recognition Letters 107, 3-16	539	2018
A multimodal approach for human activity recognition based on skeleton and RGB data A Franco, A Magnani, D Maio Pattern Recognition Letters 131, 293-299	421	2020
Classification of myocardial infarction with multi-lead ECG signals and deep CNN UB Baloglu, M Talo, O Yildirim, R San Tan, UR Acharya Pattern Recognition Letters 122, 23-30	333	2019
LightenNet: A Convolutional Neural Network for weakly illuminated image enhancement C Li, J Guo, F Porikli, Y Pang Pattern Recognition Letters 104, 15-22	293	2018
Deep-ECG: Convolutional Neural Networks for ECG biometric recognition RD Labati, E Muñoz, V Piuri, R Sassi, F Scotti Pattern Recognition Letters 126, 78-85	290	2019
Deep-learning framework to detect lung abnormality–A study with chest X-Ray and lung CT scan images A Bhandary, GA Prabhu, V Rajinikanth, KP Thanaraj, SC Satapathy, ... Pattern Recognition Letters 129, 271-278	288	2020
A study of deep convolutional auto-encoders for anomaly detection in videos M Ribeiro, AE Lazzaretti, HS Lopes Pattern Recognition Letters 105, 13-22	288	2018
Foreground segmentation using convolutional neural networks for multiscale feature encoding LA Lim, HY Keles Pattern Recognition Letters 112, 256-262	273	2018
Comparative analysis of image classification algorithms based on traditional machine learning and deep learning P Wang, E Fan, P Wang Pattern Recognition Letters 141, 61-67	267	2021
Unsupervised skin tissue segmentation for remote photoplethysmography S Bobbia, R Macwan, Y Benezeth, A Mansouri, J Dubois Pattern Recognition Letters 124, 82-90	266	2019
Extended deep neural network for facial emotion recognition DK Jain, P Shamsolmoali, P Sehdev Pattern Recognition Letters 120, 69-74	264	2019
A note on the triangle inequality for the Jaccard distance S Kosub Pattern Recognition Letters 120, 36-38	263	2019
A review of Convolutional-Neural-Network-based action recognition G Yao, T Lei, J Zhong Pattern Recognition Letters 118, 14-22	262	2019
A light CNN for detecting COVID-19 from CT scans of the chest M Polsinelli, L Cinque, G Placidi Pattern Recognition Letters 140, 95-100	253	2020
Automated detection and classification of fundus diabetic retinopathy images using synergic deep learning model K Shankar, ARW Sait, D Gupta, SK Lakshmanaprabu, A Khanna, ... Pattern Recognition Letters 133, 210-216	246	2020
Hybrid deep neural networks for face emotion recognition N Jain, S Kumar, A Kumar, P Shamsolmoali, M Zareapoor Pattern Recognition Letters 115, 101-106	235	2018
Automated invasive ductal carcinoma detection based using deep transfer learning with whole-slide images Y Celik, M Talo, O Yildirim, M Karabatak, UR Acharya Pattern Recognition Letters 133, 232-239	233	2020

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