Most cited papers from NEC (United States)
What are the most cited papers from NEC (United States)?
The most cited paper from NEC (United States) is "Locality-constrained Linear Coding for image classification" (Jinjun Wang, Jianchao Yang, Kai Yu et al., 2010), with 3,079 citations. Next come "Linear spatial pyramid matching using sparse coding for image classification" (2,880) and "A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction" (1,453).
Showing 50 of 59 papers. Every paper with more than 160 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Locality-constrained Linear Coding for image classification Jinjun Wang, Jianchao Yang, Kai Yu et al. | Jun 2010 | 3,079 |
| 2 | Linear spatial pyramid matching using sparse coding for image classification Jianchao Yang, Kai Yu, Yihong Gong et al. · 2009 IEEE Conference on Computer Vision and Pattern Recognition | Jun 2009 | 2,880 |
| 3 | A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction Yao Qin, Dongjin Song, Haifeng Chen et al. | 28 Jul 2017 | 1,453 |
| 4 | ONOS Pankaj Berde, Matteo Gerola, Jonathan Hart et al. | 12 Aug 2014 | 1,126 |
| 5 | DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents Namhoon Lee, Wongun Choi, Paul Vernaza et al. | Jul 2017 | 1,085 |
| 6 | A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data Chuxu Zhang, Dongjin Song, Yuncong Chen et al. · Proceedings of the AAAI Conference on Artificial Intelligence | 17 Jul 2019 | 819 |
| 7 | Exploit All the Layers: Fast and Accurate CNN Object Detector with Scale Dependent Pooling and Cascaded Rejection Classifiers Fan Yang, Wongun Choi, Yuanqing Lin | Jun 2016 | 642 |
| 8 | CHEX Long Jason Lu, Zhichun Li, Zhenyu Wu et al. | 15 Oct 2012 | 596 |
| 9 | Analysis and characterization of inherent application resilience for approximate computing Vinay K. Chippa, Srimat Chakradhar, Kaushik Roy et al. | 28 May 2013 | 549 |
| 10 | SegFlow: Joint Learning for Video Object Segmentation and Optical Flow Jingchun Cheng, Yi–Hsuan Tsai, Shengjin Wang et al. | Oct 2017 | 472 |
| 11 | Near-Online Multi-target Tracking with Aggregated Local Flow Descriptor Wongun Choi | Dec 2015 | 414 |
| 12 | Parallel support vector machines: The cascade svm Hans Peter Graf, Eric Cosatto, Léon Bottou et al. | 2005 | 407 |
| 13 | Large-scale image classification: Fast feature extraction and SVM training Yuanqing Lin, Fengjun Lv, Shenghuo Zhu et al. | Jun 2011 | 387 |
| 14 | Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease Peter Ganz, Bettina Heidecker, Kristian Hveem et al. · JAMA | 21 Jun 2016 | 381 |
| 15 | Camouflaged Object Detection with Feature Decomposition and Edge Reconstruction Chunming He, Kai Li, Yachao Zhang et al. | Jun 2023 | 377 |
| 16 | Evolutionary spectral clustering by incorporating temporal smoothness Yün Chi, Xiaodan Song, Dengyong Zhou et al. | 12 Aug 2007 | 370 |
| 17 | Supervised translation-invariant sparse coding Jianchao Yang, Kai Yu, Thomas S. Huang | Jun 2010 | 362 |
| 18 | Human Tracking Using Convolutional Neural Networks Jialue Fan, Wei Hong Xu, Ying Nian Wu et al. · IEEE Transactions on Neural Networks | Sep 2010 | 361 |
| 19 | Towards Large-Pose Face Frontalization in the Wild Xi Peng Yin, Yu Xiang, Kihyuk Sohn et al. | Oct 2017 | 357 |
| 20 | Feature Transfer Learning for Face Recognition With Under-Represented Data Xi Peng Yin, Yu Xiang, Kihyuk Sohn et al. | Jun 2019 | 355 |
| 21 | Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms Dinghan Shen, Guoyin Wang, Wenlin Wang et al. | 2018 | 332 |
| 22 | The Bloomier filter: an efficient data structure for static support lookup tables Bernard Chazelle, Joe Kilian, Ronitt Rubinfeld et al. | 11 Jan 2004 | 332 |
| 23 | Weakly-Supervised Semantic Segmentation via Sub-Category Exploration Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung et al. | Jun 2020 | 320 |
| 24 | Fast and Accurate Online Video Object Segmentation via Tracking Parts Jingchun Cheng, Yi–Hsuan Tsai, Wei-Chih Hung et al. | Jun 2018 | 303 |
| 25 | Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization Dingding Wang, Tao Li, Shenghuo Zhu et al. | 20 Jul 2008 | 295 |
| 26 | Radio access network virtualization for future mobile carrier networks Xavier Costa‐Pérez, Joerg Swetina, Tao Guo et al. · IEEE Communications Magazine | Jul 2013 | 291 |
| 27 | Soft Edge Smoothness Prior for Alpha Channel Super Resolution Shengyang Dai, Mei Han, Wei Hong Xu et al. | Jun 2007 | 268 |
| 28 | FlowSense: Monitoring Network Utilization with Zero Measurement Cost Curtis Yu, Cristian Lumezanu, Yueping Zhang et al. · Lecture notes in computer science | 2013 | 265 |
| 29 | Key Technologies of WDM-PON for Future Converged Optical Broadband Access Networks [Invited] Gee‐Kung Chang, Arshad Chowdhury, Zhensheng Jia et al. · Journal of Optical Communications and Networking | 24 Aug 2009 | 258 |
| 30 | Using Channel Hopping to Increase 802.11 Resilience to Jamming Attacks Vishnu Navda, A. Bohra, Sourav Ganguly et al. | 2007 | 256 |
| 31 | Quality programmable vector processors for approximate computing Swagath Venkataramani, Vinay K. Chippa, Srimat Chakradhar et al. | 7 Dec 2013 | 253 |
| 32 | Approximate computing and the quest for computing efficiency Swagath Venkataramani, Srimat Chakradhar, Kaushik Roy et al. | 2 Jun 2015 | 249 |
| 33 | Fine-Grained Categorization and Dataset Bootstrapping Using Deep Metric Learning with Humans in the Loop Yin Cui, Feng Zhou, Yuanqing Lin et al. | Jun 2016 | 244 |
| 34 | Beyond spatial pyramids: Receptive field learning for pooled image features Yangqing Jia, Chang Huang, T. Darrell | Jun 2012 | 239 |
| 35 | r2p2: A ReparameteRized Pushforward Policy for Diverse, Precise Generative Path Forecasting Nicholas Rhinehart, Kris Kitani, Paul Vernaza · Lecture notes in computer science | 2018 | 237 |
| 36 | Every Pixel Matters: Center-Aware Feature Alignment for Domain Adaptive Object Detector Cheng-Chun Hsu, Yi–Hsuan Tsai, Yen‐Yu Lin et al. · Lecture notes in computer science | 2020 | 233 |
| 37 | Efficient Object Detection and Segmentation for Fine-Grained Recognition Anelia Angelova, Shenghuo Zhu | Jun 2013 | 231 |
| 38 | Embedding Label Structures for Fine-Grained Feature Representation Xiaofan Zhang, Feng Zhou, Yuanqing Lin et al. | Jun 2016 | 218 |
| 39 | SoftCuts: A Soft Edge Smoothness Prior for Color Image Super-Resolution Shengyang Dai, Mei Han, Wei Xu et al. · IEEE Transactions on Image Processing | 31 Mar 2009 | 218 |
| 40 | Learning image representations from the pixel level via hierarchical sparse coding Kai Yu, Yuanqing Lin, John Lafferty | Jun 2011 | 216 |
| 41 | Blog Community Discovery and Evolution Based on Mutual Awareness Expansion Yu‐Ru Lin, Hari Sundaram, Yün Chi et al. | Nov 2007 | 204 |
| 42 | BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion Fu-En Wang, Yu-Hsuan Yeh, Min Sun et al. | Jun 2020 | 203 |
| 43 | HYDRAstor: a Scalable Secondary Storage Cezary Dubnicki, Leszek Gryz, Lukasz Heldt et al. · File and Storage Technologies | 24 Feb 2009 | 201 |
| 44 | 3D Convolutional Neural Networks for Human Action Recognition Shuiwang Ji, Wei Hong Xu, Ming Juan Yang et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence | 6 Mar 2012 | 194 |
| 45 | Towards a Timely Causality Analysis for Enterprise Security Yushan Liu, Mu Zhang, Li Ding et al. | 2018 | 187 |
| 46 | Incremental Learning Using Conditional Adversarial Networks Ye Xiang, Ying Fu, Pan Ji et al. | Oct 2019 | 186 |
| 47 | Query Specific Fusion for Image Retrieval Shaoting Zhang, Ming Juan Yang, Timothée Cour et al. · Lecture notes in computer science | 2012 | 183 |
| 48 | Contextual weighting for vocabulary tree based image retrieval Xiaoyu Wang, Ming Juan Yang, Timothée Cour et al. | Nov 2011 | 177 |
| 49 | Object-Centric Spatial Pooling for Image Classification Olga Russakovsky, Yuanqing Lin, Kai Yu et al. · Lecture notes in computer science | 2012 | 176 |
| 50 | Scalable effort hardware design Vinay K. Chippa, Debabrata Mohapatra, Anand Raghunathan et al. | 13 Jun 2010 | 174 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.