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ORCIDPouria Sadeghi-Tehran
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2020 – today
- 2021
[j5]Pouria Sadeghi-Tehran
, Nicolas Virlet, Malcolm J. Hawkesford:
A Neural Network Method for Classification of Sunlit and Shaded Components of Wheat Canopies in the Field Using High-Resolution Hyperspectral Imagery. Remote. Sens. 13(5): 898 (2021)- [i2]Etienne David, Mario Serouart, Daniel Smith, Simon Madec, Kaaviya Velumani, Shouyang Liu, Xu Wang, Francisco Pinto Espinosa, Shahameh Shafiee, Izzat S. A. Tahir, Hisashi Tsujimoto, Shuhei Nasuda, Bangyou Zheng, Norbert Kichgessner, Helge Aasen, Andreas Hund, Pouria Sadeghi-Tehran, Koichi Nagasawa, Goro Ishikawa, Sébastien Dandrifosse, Alexis Carlier, Benoit Mercatoris, Ken Kuroki, Haozhou Wang, Masanori Ishii, Minhajul A. Badhon, Curtis Pozniak, David Shaner LeBauer, Morten Lilimo, Jesse Poland, Scott C. Chapman, Benoit de Solan, Frédéric Baret, Ian Stavness, Wei Guo:
Global Wheat Head Dataset 2021: an update to improve the benchmarking wheat head localization with more diversity. CoRR abs/2105.07660 (2021) - 2020
- [i1]Etienne David, Simon Madec, Pouria Sadeghi-Tehran, Helge Aasen, B. Zheng, Shouyang Liu, Norbert Kirchgeßner, Goro Ishikawa, Koichi Nagasawa, Minhajul A. Badhon, Curtis Pozniak, Benoit de Solan, Andreas Hund, Scott C. Chapman, Frédéric Baret, Ian Stavness, Wei Guo:
Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods. CoRR abs/2005.02162 (2020)
2010 – 2019
- 2019
- [j4]Pouria Sadeghi-Tehran, Plamen Angelov, Nicolas Virlet, Malcolm J. Hawkesford:
Scalable Database Indexing and Fast Image Retrieval Based on Deep Learning and Hierarchically Nested Structure Applied to Remote Sensing and Plant Biology. J. Imaging 5(3): 33 (2019) - 2017
- [j3]Plamen Angelov, Pouria Sadeghi-Tehran:
Look-a-Like: A Fast Content-Based Image Retrieval Approach Using a Hierarchically Nested Dynamically Evolving Image Clouds and Recursive Local Data Density. Int. J. Intell. Syst. 32(1): 82-103 (2017) - [j2]Plamen Angelov, Pouria Sadeghi-Tehran, Christopher Clarke:
AURORA: autonomous real-time on-board video analytics. Neural Comput. Appl. 28(5): 855-865 (2017) - 2015
- [c9]Plamen Angelov, Pouria Sadeghi-Tehran:
A Nested Hierarchy of Dynamically Evolving Clouds for Big Data Structuring and Searching. INNS Conference on Big Data 2015: 1-8 - 2014
- [c8]Pouria Sadeghi-Tehran, Christopher Clarke, Plamen Angelov:
A real-time approach for autonomous detection and tracking of moving objects from UAV. EALS 2014: 43-49 - [c7]Pouria Sadeghi-Tehran, Plamen Angelov:
ATDT: Autonomous Template-Based Detection and Tracking of Objects from Airborne Camera. IEEE Conf. on Intelligent Systems (2) 2014: 555-565 - 2012
- [b1]Pouria Sadeghi-Tehran:
Automatic methods for videostreams analysis and self-evolving controllers. Lancaster University, UK, 2012 - [c6]Pouria Sadeghi-Tehran, Sasmita Behera, Plamen Angelov, Javier Andreu:
Autonomous visual self-localization in completely unknown environment. EAIS 2012: 90-95 - [c5]Pouria Sadeghi-Tehran, Plamen Angelov:
A real-time approach for novelty detection and trajectories analysis for anomaly recognition in video surveillance systems. EAIS 2012: 108-113 - [c4]Pouria Sadeghi-Tehran, Ana Belén Cara, Plamen Angelov, Héctor Pomares, Ignacio Rojas, Alberto Prieto:
Self-evolving parameter-free Rule-based Controller. FUZZ-IEEE 2012: 1-8 - [c3]Plamen Angelov, Chirag Gude, Pouria Sadeghi-Tehran, Tsvetan Ivanov:
ARTOT: Autonomous real-time object detection and tracking by a moving camera. IEEE Conf. of Intelligent Systems 2012: 446-452 - 2011
- [j1]Plamen Angelov, Pouria Sadeghi-Tehran, Ramin Ramezani:
An approach to automatic real-time novelty detection, object identification, and tracking in video streams based on recursive density estimation and evolving Takagi-Sugeno fuzzy systems. Int. J. Intell. Syst. 26(3): 189-205 (2011) - [c2]Pouria Sadeghi-Tehran, Plamen Angelov:
Online self-evolving fuzzy controller for autonomous mobile robots. EAIS 2011: 100-107 - 2010
- [c1]Pouria Sadeghi-Tehran, Plamen Angelov, Ramin Ramezani:
A Fast Recursive Approach to Autonomous Detection, Identification and Tracking of Multiple Objects in Video Streams under Uncertainties. IPMU (2) 2010: 30-43
Coauthor Index
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