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Mahsa Baktash
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2020 – today
- 2024
- [c49]Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann:
Source-Free Domain-Invariant Performance Prediction. ECCV (80) 2024: 99-116 - [c48]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. SIGIR 2024: 1307-1317 - [c47]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. SIGIR 2024: 2739-2743 - [c46]Nikhil Reddy, Mahsa Baktashmotlagh, Chetan Arora:
Domain-Aware Knowledge Distillation for Continual Model Generalization. WACV 2024: 685-696 - [i40]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Leveraging LLMs for Unsupervised Dense Retriever Ranking. CoRR abs/2402.04853 (2024) - [i39]Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh, Zi Huang, Yadan Luo:
MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection. CoRR abs/2406.14878 (2024) - [i38]Jia Syuen Lim, Zhuoxiao Chen, Mahsa Baktashmotlagh, Zhi Chen, Xin Yu, Zi Huang, Yadan Luo:
DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection. CoRR abs/2406.14924 (2024) - [i37]Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon:
Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. CoRR abs/2407.06685 (2024) - [i36]Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann:
Source-Free Domain-Invariant Performance Prediction. CoRR abs/2408.02209 (2024) - [i35]Sean M. V. Collins, Brendan Tidd, Mahsa Baktashmotlagh, Peyman Moghadam:
Shape-Space Deformer: Unified Visuo-Tactile Representations for Robotic Manipulation of Deformable Objects. CoRR abs/2409.12419 (2024) - 2023
- [j8]Siamak Layeghy, Mahsa Baktashmotlagh, Marius Portmann:
DI-NIDS: Domain invariant network intrusion detection system. Knowl. Based Syst. 273: 110626 (2023) - [j7]Yadan Luo, Zijian Wang, Zhuoxiao Chen, Zi Huang, Mahsa Baktashmotlagh:
Source-Free Progressive Graph Learning for Open-Set Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 45(9): 11240-11255 (2023) - [j6]Yadan Luo, Zi Huang, Hongxu Chen, Yang Yang, Hongzhi Yin, Mahsa Baktashmotlagh:
Interpretable Signed Link Prediction With Signed Infomax Hyperbolic Graph. IEEE Trans. Knowl. Data Eng. 35(4): 3991-4002 (2023) - [c45]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Convolutional Persistence as a Remedy to Neural Model Analysis. AISTATS 2023: 10839-10855 - [c44]Zhuoxiao Chen, Yadan Luo, Zheng Wang, Mahsa Baktashmotlagh, Zi Huang:
Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling. ICCV 2023: 3691-3703 - [c43]Zijian Wang, Yadan Luo, Liang Zheng, Zi Huang, Mahsa Baktashmotlagh:
How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability. ICCV 2023: 5526-5535 - [c42]Mateusz Michalkiewicz, Masoud Faraki, Xiang Yu, Manmohan Chandraker, Mahsa Baktashmotlagh:
Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters. ICCV 2023: 6154-6165 - [c41]Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Mahsa Baktashmotlagh, Zi Huang:
Kecor: Kernel Coding Rate Maximization for Active 3D Object Detection. ICCV 2023: 18233-18244 - [c40]Yadan Luo, Zhuoxiao Chen, Zijian Wang, Xin Yu, Zi Huang, Mahsa Baktashmotlagh:
Exploring Active 3D Object Detection from a Generalization Perspective. ICLR 2023 - [c39]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. SIGIR-AP 2023: 223-233 - [c38]Zijian Wang, Yadan Luo, Zi Huang, Mahsa Baktashmotlagh:
FFM: Injecting Out-of-Domain Knowledge via Factorized Frequency Modification. WACV 2023: 4124-4133 - [c37]Tianle Chen, Mahsa Baktashmotlagh, Zijian Wang, Mathieu Salzmann:
Center-aware Adversarial Augmentation for Single Domain Generalization. WACV 2023: 4146-4154 - [i34]Yadan Luo, Zhuoxiao Chen, Zijian Wang, Xin Yu, Zi Huang, Mahsa Baktashmotlagh:
Exploring Active 3D Object Detection from a Generalization Perspective. CoRR abs/2301.09249 (2023) - [i33]Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Zi Huang, Mahsa Baktashmotlagh:
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection. CoRR abs/2307.07942 (2023) - [i32]Zhuoxiao Chen, Yadan Luo, Zi Huang, Zheng Wang, Mahsa Baktashmotlagh:
Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling. CoRR abs/2307.07944 (2023) - [i31]Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon:
Selecting which Dense Retriever to use for Zero-Shot Search. CoRR abs/2309.09403 (2023) - [i30]Mateusz Michalkiewicz, Masoud Faraki, Xiang Yu, Manmohan Chandraker, Mahsa Baktashmotlagh:
Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters. CoRR abs/2310.07361 (2023) - 2022
- [c36]Philip Hawkins, Frédéric Maire, Simon Denman, Mahsa Baktashmotlagh:
Modular Construction Planning Using Graph Neural Network Heuristic Search. AI 2022: 228-239 - [c35]Nikhil Reddy, Abhinav Singhal, Abhishek Kumar, Mahsa Baktashmotlagh, Chetan Arora:
Master of All: Simultaneous Generalization of Urban-Scene Segmentation to All Adverse Weather Conditions. ECCV (39) 2022: 51-69 - [c34]Tianle Chen, Mahsa Baktashmotlagh, Mathieu Salzmann:
Contrastive Class-aware Adaptation for Domain Generalization. ICPR 2022: 4871-4876 - [c33]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Rethinking Persistent Homology For Visual Recognition. TAG-ML 2022: 206-215 - [c32]Mahsa Baktashmotlagh, Tianle Chen, Mathieu Salzmann:
Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift. WACV 2022: 3737-3746 - [i29]Yadan Luo, Zijian Wang, Zhuoxiao Chen, Zi Huang, Mahsa Baktashmotlagh:
Source-Free Progressive Graph Learning for Open-Set Domain Adaptation. CoRR abs/2202.06174 (2022) - [i28]Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Rethinking Persistent Homology for Visual Recognition. CoRR abs/2207.04220 (2022) - [i27]Siamak Layeghy, Mahsa Baktashmotlagh, Marius Portmann:
DI-NIDS: Domain Invariant Network Intrusion Detection System. CoRR abs/2210.08252 (2022) - 2021
- [j5]Ahmed Al-Saffar, Alina Bialkowski, Mahsa Baktashmotlagh, Adnan Trakic, Lei Guo, Amin M. Abbosh:
Closing the Gap of Simulation to Reality in Electromagnetic Imaging of Brain Strokes via Deep Neural Networks. IEEE Trans. Computational Imaging 7: 13-21 (2021) - [c31]Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Gholamreza Haffari, Mahsa Baktashmotlagh:
Neural-Symbolic Commonsense Reasoner with Relation Predictors. ACL/IJCNLP (2) 2021: 797-802 - [c30]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Asia O. Armstrong, Mahsa Baktashmotlagh:
Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings. DICTA 2021: 1-8 - [c29]Zijian Wang, Yadan Luo, Ruihong Qiu, Zi Huang, Mahsa Baktashmotlagh:
Learning to Diversify for Single Domain Generalization. ICCV 2021: 814-823 - [c28]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh:
Semi-supervised Keypoint Localization. ICLR 2021 - [c27]Zhuoxiao Chen, Yadan Luo, Mahsa Baktashmotlagh:
Conditional Extreme Value Theory for Open Set Video Domain Adaptation. MMAsia 2021: 20:1-20:8 - [c26]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh:
Keypoint-Aligned Embeddings for Image Retrieval and Re-identification. WACV 2021: 676-685 - [i26]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh:
Semi-supervised Keypoint Localization. CoRR abs/2101.07988 (2021) - [i25]Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Gholamreza Haffari, Mahsa Baktashmotlagh:
Neural-Symbolic Commonsense Reasoner with Relation Predictors. CoRR abs/2105.06717 (2021) - [i24]Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky:
Learning Compositional Shape Priors for Few-Shot 3D Reconstruction. CoRR abs/2106.06440 (2021) - [i23]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh:
Going Deeper into Semi-supervised Person Re-identification. CoRR abs/2107.11566 (2021) - [i22]Zijian Wang, Yadan Luo, Ruihong Qiu, Zi Huang, Mahsa Baktashmotlagh:
Learning to Diversify for Single Domain Generalization. CoRR abs/2108.11726 (2021) - [i21]Zhuoxiao Chen, Yadan Luo, Mahsa Baktashmotlagh:
Conditional Extreme Value Theory for Open Set Video Domain Adaptation. CoRR abs/2109.00522 (2021) - 2020
- [j4]Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan:
Correlation-aware adversarial domain adaptation and generalization. Pattern Recognit. 100: 107124 (2020) - [c25]Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh, Yang Yang:
Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks. AAAI 2020: 5021-5028 - [c24]Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders P. Eriksson:
A Simple and Scalable Shape Representation for 3D Reconstruction. BMVC 2020 - [c23]Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Mahsa Baktashmotlagh, Gholamreza Haffari:
CosMo: Conditional Seq2Seq-based Mixture Model for Zero-Shot Commonsense Question Answering. COLING 2020: 5347-5359 - [c22]Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky:
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. ECCV (25) 2020: 614-630 - [c21]Yadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh:
Progressive Graph Learning for Open-Set Domain Adaptation. ICML 2020: 6468-6478 - [c20]Yadan Luo, Zi Huang, Zijian Wang, Zheng Zhang, Mahsa Baktashmotlagh:
Adversarial Bipartite Graph Learning for Video Domain Adaptation. ACM Multimedia 2020: 19-27 - [c19]Zijian Wang, Yadan Luo, Zi Huang, Mahsa Baktashmotlagh:
Prototype-Matching Graph Network for Heterogeneous Domain Adaptation. ACM Multimedia 2020: 2104-2112 - [c18]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh:
Learning Landmark Guided Embeddings for Animal Re-identification. WACV Workshops 2020: 12-19 - [p2]Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan:
On Minimum Discrepancy Estimation for Deep Domain Adaptation. Domain Adaptation for Visual Understanding 2020: 81-94 - [i20]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh:
Learning landmark guided embeddings for animal re-identification. CoRR abs/2001.02801 (2020) - [i19]Qianggong Zhang, Yanyang Gu, Mateusz Michalkiewicz, Mahsa Baktashmotlagh, Anders P. Eriksson:
Implicitly Defined Layers in Neural Networks. CoRR abs/2003.01822 (2020) - [i18]Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky:
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. CoRR abs/2004.06302 (2020) - [i17]Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders P. Eriksson:
A Simple and Scalable Shape Representation for 3D Reconstruction. CoRR abs/2005.04623 (2020) - [i16]Yadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh:
Progressive Graph Learning for Open-Set Domain Adaptation. CoRR abs/2006.12087 (2020) - [i15]Yadan Luo, Zi Huang, Zijian Wang, Zheng Zhang, Mahsa Baktashmotlagh:
Adversarial Bipartite Graph Learning for Video Domain Adaptation. CoRR abs/2007.15829 (2020) - [i14]Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh:
Keypoint-Aligned Embeddings for Image Retrieval and Re-identification. CoRR abs/2008.11368 (2020) - [i13]Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Mahsa Baktashmotlagh, Gholamreza Haffari:
COSMO: Conditional SEQ2SEQ-based Mixture Model for Zero-Shot Commonsense Question Answering. CoRR abs/2011.00777 (2020) - [i12]Yadan Luo, Zi Huang, Hongxu Chen, Yang Yang, Mahsa Baktashmotlagh:
Interpretable Signed Link Prediction with Signed Infomax Hyperbolic Graph. CoRR abs/2011.12517 (2020) - [i11]Farhad Moghimifar, Afshin Rahimi, Mahsa Baktashmotlagh, Xue Li:
Learning Causal Bayesian Networks from Text. CoRR abs/2011.13115 (2020) - [i10]Farhad Moghimifar, Gholamreza Haffari, Mahsa Baktashmotlagh:
Domain Adaptative Causality Encoder. CoRR abs/2011.13549 (2020)
2010 – 2019
- 2019
- [j3]Samuel Cunningham-Nelson, Mahsa Baktashmotlagh, Wageeh W. Boles:
Visualizing Student Opinion Through Text Analysis. IEEE Trans. Educ. 62(4): 305-311 (2019) - [c17]Philip Hawkins, Frédéric Maire, Simon Denman, Mahsa Baktashmotlagh:
Object Graph Networks for Spatial Language Grounding. DICTA 2019: 1-8 - [c16]Mateusz Michalkiewicz, Jhony Kaesemodel Pontes, Dominic Jack, Mahsa Baktashmotlagh, Anders P. Eriksson:
Implicit Surface Representations As Layers in Neural Networks. ICCV 2019: 4742-4751 - [c15]Mahsa Baktashmotlagh, Masoud Faraki, Tom Drummond, Mathieu Salzmann:
Learning Factorized Representations for Open-Set Domain Adaptation. ICLR (Poster) 2019 - [c14]Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan:
Multi-Component Image Translation for Deep Domain Generalization. WACV 2019: 579-588 - [i9]Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan:
On Minimum Discrepancy Estimation for Deep Domain Adaptation. CoRR abs/1901.00282 (2019) - [i8]Mateusz Michalkiewicz, Jhony K. Pontes, Dominic Jack, Mahsa Baktashmotlagh, Anders P. Eriksson:
Deep Level Sets: Implicit Surface Representations for 3D Shape Inference. CoRR abs/1901.06802 (2019) - [i7]Olga Moskvyak, Frédéric Maire, Asia O. Armstrong, Feras Dayoub, Mahsa Baktashmotlagh:
Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings. CoRR abs/1902.10847 (2019) - [i6]Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh, Yang Yang:
Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling. CoRR abs/1911.04695 (2019) - [i5]Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan:
Correlation-aware Adversarial Domain Adaptation and Generalization. CoRR abs/1911.12983 (2019) - 2018
- [i4]Mahsa Baktashmotlagh, Masoud Faraki, Tom Drummond, Mathieu Salzmann:
Learning Factorized Representations for Open-set Domain Adaptation. CoRR abs/1805.12277 (2018) - [i3]Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan:
Multi-component Image Translation for Deep Domain Generalization. CoRR abs/1812.08974 (2018) - 2017
- [c13]Sarah M. Erfani, Mahsa Baktashmotlagh, Masud Moshtaghi, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao:
From Shared Subspaces to Shared Landmarks: A Robust Multi-Source Classification Approach. AAAI 2017: 1854-1860 - [c12]Afsaneh Ghasemi, Mahsa Baktashmotlagh, Simon Denman, Sridha Sridharan, Dung Nguyen Tien, Clinton Fookes:
Deep discovery of facial motions using a shallow embedding layer. ICIP 2017: 1567-1571 - [c11]Ahmed Kamil Hasan Al-Ali, David Dean, Bouchra Senadji, Mahsa Baktashmotlagh, Vinod Chandran:
Speaker verification with multi-run ICA based speech enhancement. ICSPCS 2017: 1-7 - [p1]Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Mathieu Salzmann:
Learning Domain Invariant Embeddings by Matching Distributions. Domain Adaptation in Computer Vision Applications 2017: 95-114 - [i2]Samuel Cunningham-Nelson, Mahsa Baktashmotlagh, Wageeh W. Boles:
From Review to Rating: Exploring Dependency Measures for Text Classification. CoRR abs/1709.00813 (2017) - 2016
- [j2]Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Mathieu Salzmann:
Distribution-Matching Embedding for Visual Domain Adaptation. J. Mach. Learn. Res. 17: 108:1-108:30 (2016) - [c10]Sarah M. Erfani, Mahsa Baktashmotlagh, Masud Moshtaghi, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao:
Robust Domain Generalisation by Enforcing Distribution Invariance. IJCAI 2016: 1455-1461 - [c9]Sarah M. Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao:
R1STM: One-class Support Tensor Machine with Randomised Kernel. SDM 2016: 198-206 - 2015
- [c8]Sarah M. Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Shanika Karunasekera, Christopher Leckie:
R1SVM: A Randomised Nonlinear Approach to Large-Scale Anomaly Detection. AAAI 2015: 432-438 - [c7]Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Mahsa Baktashmotlagh:
Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs. ICCV 2015: 4112-4120 - [i1]Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Mahsa Baktashmotlagh:
Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs. CoRR abs/1507.08711 (2015) - 2014
- [b1]Mahsa Baktashmotlagh:
Learning Invariances for High-Dimensional Data Analysis. University of Queensland, Australia, 2014 - [j1]Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Brian C. Lovell, Mathieu Salzmann:
Discriminative Non-Linear Stationary Subspace Analysis for Video Classification. IEEE Trans. Pattern Anal. Mach. Intell. 36(12): 2353-2366 (2014) - [c6]Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Brian C. Lovell, Mathieu Salzmann:
Domain Adaptation on the Statistical Manifold. CVPR 2014: 2481-2488 - 2013
- [c5]Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Brian C. Lovell, Mathieu Salzmann:
Unsupervised Domain Adaptation by Domain Invariant Projection. ICCV 2013: 769-776 - [c4]Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Abbas Bigdeli, Brian C. Lovell, Mathieu Salzmann:
Non-Linear Stationary Subspace Analysis with Application to Video Classification. ICML (3) 2013: 450-458 - 2012
- [c3]Ehsan Norouznezhad, Mehrtash Tafazzoli Harandi, Abbas Bigdeli, Mahsa Baktash, Adam Postula, Brian C. Lovell:
Directional Space-Time Oriented Gradients for 3D Visual Pattern Analysis. ECCV (3) 2012: 736-749 - [c2]Amin Ahmadi, Abbas Bigdeli, Mahsa Baktashmotlagh, Brian C. Lovell:
A wireless mesh sensor network for hazard and safety monitoring at the Port of Brisbane. LCN 2012: 180-183 - 2011
- [c1]Mahsa Baktashmotlagh, Abbas Bigdeli, Brian C. Lovell:
Dynamic resource aware sensor networks: Integration of sensor cloud and ERPs. AVSS 2011: 455-460
Coauthor Index
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