Staff profile

Professor Paolo Remagnino has worked in computer vision and artificial intelligence for over 30 years. Professor Remagnino research is on the development of innovative methods for image and video interpretation, making wide use of pattern recognition, machine and deep learning and distributed intelligence techniques. Professor Remagnino has published over 180 scientific articles in international conferences and high impact journals. Prof. Remagnino has secured research grants funded by most scientific funding bodies, including the NATEP, Innovate UK, EPSRC, MRC, Leverhulme Trust, EU (FP7 and H2020) and the US DHS. At present, Prof. Remagnino is the principal investigator of a project on the development of machine learning algorithms for the automatic assessment of the health of natural habitats (https://www.nih2020.eu/).

• Image and Video Analysis
• Artificial intelligence
• Machine Learning
• Pattern Recognition
• Physical Security

• 0000: : UK Research and Innovation Fellowships Peer Review College member
• 0000: : JSPS fellow ;
• 0000: : EPRSC college ;
• 0000: : Visiting Researcher at the Royal Botanic Gardens, Kew ;

Available for media contact about:

• Computer Science:
• Computer Science: image and video analytics, pattern recognition, artificial intelligence, machine learning

Conference Paper

• Lim, Jian Han, Tan, Chun Shui, Chan, Chee Seng, Welikala, Roshan Alex, Remagnino, Paolo, Rajendran, Senthilmani, Kallarakkal, Thomas George, Zain, Rosnah Binti, Jayasinghe, Ruwan Duminda, Rimal, Jyotsna, Kerr, Alexander Ross, Amtha, Rahmi, Patil, Karthikeya, Tilakaratne, Wanninayake Mudiyanselage, Gibson, John, Cheong, Sok Ching & Barman, Sarah Ann (2021), D'OraCa: Deep Learning-Based Classification of Oral Lesions with Mouth Landmark Guidance for Early Detection of Oral Cancer, in Papiez, BW, Yaqub, M, Jiao, J, Namburete, AIL & Noble, JA eds, Lecture Notes in Computer Science 12722: MEDICAL IMAGE UNDERSTANDING AND ANALYSIS (MIUA 2021) Univ Oxford; Univ Oxford, Med Sci Div, Nuffield Dept Clin Neurosciences; Big Data Inst; Math Phys \& Life Sci Div; Inst Biomed Engn; MathWorks; Brainomix; Journal Imaging; Oxford Univ Innovat; nVidia; I. 408-422.
• Saeed, R. A., Recupero, Diego Reforgiato & Remagnino, Paolo (2021), Simulating People Dynamics, International Conference on Intelligent Environments 2021 17TH INTERNATIONAL CONFERENCE ON INTELLIGENT ENVIRONMENTS (IE) IEEE; Middlesex Univ London; Sapienza Univ Roma; Univ Grenoble Alpes; Queensland Univ Technol; IEEE Syst Man \& Cybernet Soc; IOS Press; Assoc Advancement Artificial Intelligence; Technol.
• Khadka, A., Remagnino, P. & Argyriou, V (2020), SYNTHETIC CROWD AND PEDESTRIAN GENERATOR FOR DEEP LEARNING PROBLEMS, International Conference on Acoustics Speech and Signal Processing ICASSP 2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING Inst Elect \& Elect Engineers; Inst Elect \& Elect Engineers, Signal Proc Soc. 4052-4056.
• Khadka, Anish, Argyriou, Vasileios & Remagnino, Paolo (2020), Accurate Deep Net Crowd Counting for Smart IoT Video acquisition devices, IEEE International Conference on Distributed Computing in Sensor Systems 16TH ANNUAL INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SENSOR SYSTEMS (DCOSS 2020) IEEE Comp Soc. 260-264.
• Kerdegari, Hamideh, Razaak, Manzoor, Argyriou, Vasileios & Remagnino, Paolo (2019), Smart Monitoring of Crops Using Generative Adversarial Networks, in Vento, M & Percannella, G eds, Lecture Notes in Computer Science 11678: COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2019, PT I Univ Salerno, Dept Comp \& Elect Engn \& Appl Math; SAST Gmbh; A I Tech srl; AI4Health srl; Nexsoft spa; Gesan srl; Hanwha Techwin Europe Ltd; Springer Lecture Notes Comp Sci; Italian Assoc Comp Vi. 554-563.
• Fajtl, Jiri, Argyriou, Vasileios, Monekosso, Dorothy & Remagnino, Paolo (2019), Latent Bernoulli Autoencoder, 25TH AMERICAS CONFERENCE ON INFORMATION SYSTEMS (AMCIS 2019) Assoc Informat Syst.
• Razaak, Manzoor, Kerdegari, Hamideh, Argyriou, Vasileios & Remagnino, Paolo (2019), Multi-scale Feature Fused Single Shot Detector for Small Object Detection in UAV Images, in Tzovaras, D, Giakoumis, D, Vincze, M & Argyros, A eds, Lecture Notes in Computer Science 11754: COMPUTER VISION SYSTEMS (ICVS 2019). 778-786.
• Kerdegari, Hamideh, Razaak, Manzoor, Argyriou, Vasileios & Remagnino, Paolo (2019), Urban Scene Segmentation using Semi-supervised GAN, in Bruzzone, L, Bovolo, F & Benediktsson, JA eds, Proceedings of SPIE 11155: IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XXV SPIE.
• Oghaz, Mahdi Maktabdar, Razaak, Manzoor, Kerdegari, Hamideh, Argyriou, Vasileios & Remagnino, Paolo (2019), Scene and Environment Monitoring Using Aerial Imagery and Deep Learning, IEEE International Conference on Distributed Computing in Sensor Systems 2019 15TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SENSOR SYSTEMS (DCOSS) IEEE Comp Soc. 362-369.
• Kim, Chloe Eunhyang, Oghaz, Mandi Maktab Dar, Fajtl, Jiri, Argyriou, Vasileios & Remagnino, Paolo (2019), A Comparison of Embedded Deep Learning Methods for Person Detection, in Tremeau, A, Farinella, GM & Braz, J eds, PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 5. 459-465.
• Razaak, Manzoor, Kerdegari, Hamideh, Davies, Eleanor, Abozariba, Raouf, Broadbent, Matthew, Mason, Katy, Argyriou, Vasileios & Remagnino, Paolo (2019), An Integrated Precision Farming Application Based on 5G, UAV and Deep Learning Technologies, in Vento, M & Percannella, G eds, Communications in Computer and Information Science 1089: COMPUTER ANALYSIS OF IMAGES AND PATTERNS (CAIP 2019) Univ Salerno, Dept Comp \& Elect Engn \& Appl Math, Intelligent Machines Recognit Video Images \& Audio Lab; A I Tech srl; SAST Gmbh; AI4Health srl; Gesan srl; Hanwha Techwin Europe Ltd; Nexsoft SpA. 109-119.
• Rimboux, Antoine, Dupre, Rob, Daci, Eldriona, Lagkas, Thomas, Sarigiannidis, Panagiotis, Remagnino, Paolo & Argyriou, Vasileios (2019), Smart IoT Cameras for Crowd Analysis based on augmentation for automatic pedestrian detection, simulation and annotation, IEEE International Conference on Distributed Computing in Sensor Systems 2019 15TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SENSOR SYSTEMS (DCOSS) IEEE Comp Soc. 304-311.
• Khadka, Anish R., Remagnino, Paolo & Argyriou, Vasileios (2018), Object 3D Reconstruction based on Photometric Stereo and Inverted Rendering, in DiBaja, GS, Gallo, L, Yetongnon, K, Dipanda, A, CastrillonSantana, M & Chbeir, R eds, 2018 14TH INTERNATIONAL CONFERENCE ON SIGNAL IMAGE TECHNOLOGY \& INTERNET BASED SYSTEMS (SITIS) IEEE Comp Soc; Univ Las Palmas Gran Canaria; Univ Milan; Univ Bourgogne, Laboratoire Electronique Image Informatique Res Grp; Natl Res Council Italy, Inst High. 208-215.
• Lee, Sue Han, Chang, Yang Loong, Chan, Chee Seng & Remagnino, Paolo (2017), HGO-CNN: HYBRID GENERIC-ORGAN CONVOLUTIONAL NEURAL NETWORK FOR MULTI-ORGAN PLANT CLASSIFICATION, IEEE International Conference on Image Processing ICIP 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) Inst Elect \& Elect Engineers; Inst Elect \& Elect Engineers Signal Proc Soc. 4462-4466.
• Lee, Sue Han, Chan, Chee Seng, Wilkin, Paul & Remagnino, Paolo (2015), DEEP-PLANT: PLANT IDENTIFICATION WITH CONVOLUTIONAL NEURAL NETWORKS, IEEE International Conference on Image Processing ICIP 2015 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) Inst Elect \& Elect Engineers; IEEE Signal Proc Soc. 452-456.
• Fraz, M. M., Remagnino, P., Hoppe, A. & Barman, S. A. (2013), Retinal image analysis aimed at extraction of vascular structure using linear discriminant classifier, INTERNATIONAL CONFERENCE ON COMPUTER MEDICAL APPLICATIONS (ICCMA' 2013) IEEE, Tunisia Sect; Dar Al Uloom Univ; N\&N Global Technologies; Future Technologies \& Innovat.
• Cope, James S. & Remagnino, Paolo (2012), Classifying Plant Leaves from Their Margins Using Dynamic Time Warping, in BlancTalon, J, Philips, W, Popescu, D, Scheunders, P & Zemcik, P eds, Lecture Notes in Computer Science 7517: ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS (ACIVS 2012) Brno Univ Technol; Camea; Ghent Univ; Honeywell; Redhat; Unis; Zoner. 258-267.
• Fraz, M. M., Remagnino, P., Hoppe, A., Uyyanonvara, B., Rudnicka, A. R., Owen, C. G. & Barman, S. A. (2012), Ensemble Classification System Applied for Retinal Vessel Segmentation on Child Images Containing Various Vessel Profiles, in Campilho, A & Kamel, M eds, Lecture Notes in Computer Science 7325: IMAGE ANALYSIS AND RECOGNITION, PT II Assoc Image \& Machine Intelligence (AIMI). 380-389.
• Cope, James S. & Remagnino, Paolo (2012), Classification of High-Dimension PDFs Using the Hungarian Algorithm, in Gimelfarb, G, Hancock, E, Imiya, A, Kuijper, A, Kudo, M, Omachi, S, Windeatt, T & Yamada, K eds, Lecture Notes in Computer Science 7626: STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION Int Assoc Pattern Recognit; Int Assoc Pattern Recognit, Tech Comm 1, Stat Pattern Recognit Tech; Int Assoc Pattern Recognit, Tech Comm 2, Struct \& Syntact Pattern Recognit; Tohoku Univ; Hiroshima. 727-733.
• Fraz, Muhammad Moazam, Remagnino, Paolo, Hoppe, Andreas, Barman, Sarah. A., Rudnicka, Alicja, Owen, Chris & Whincup, Peter (2012), A model based approach for vessel caliber measurement in retinal images, in Yetongnon, K, Chbeir, R, Dipanda, A & Gallo, L eds, 8TH INTERNATIONAL CONFERENCE ON SIGNAL IMAGE TECHNOLOGY \& INTERNET BASED SYSTEMS (SITIS 2012) IEEE Comp Soc; INCAR. 129-136.

Journal Article

• Saeed, R. A., Recupero, Diego Reforgiato & Remagnino, Paolo (2022). Simulating crowd behaviour combining both microscopic and macroscopic rules. INFORMATION SCIENCES 583: 137-158.
• Maktab Dar Oghaz, Mahdi, Razaak, Manzoor & Remagnino, Paolo (2022). Enhanced Single Shot Small Object Detector for Aerial Imagery Using Super-Resolution, Feature Fusion and Deconvolution. SENSORS 22(12): 4339.
• Saeed, Raza Abdulla, Recupero, Diego Reforgiato & Remagnino, Paolo (2021). The boundary node method for multi-robot multi-goal path planning problems. EXPERT SYSTEMS 38(6): e12691.
• Chang, Y. L., Chan, C. S. & Remagnino, P. (2021). Action recognition on continuous video. NEURAL COMPUTING \& APPLICATIONS 33(4): 1233-1243.
• Dupre, Robert, Fajtl, Jiri, Argyriou, Vasileios & Remagnino, Paolo (2020). Improving Dataset Volumes and Model Accuracy With Semi-Supervised Iterative Self-Learning. IEEE TRANSACTIONS ON IMAGE PROCESSING 29: 4337-4348.
• Welikala, Roshan Alex, Remagnino, Paolo, Lim, Jian Han, Chan, Chee Seng, Rajendran, Senthilmani, Kallarakkal, Thomas George, Zain, Rosnah Binti, Jayasinghe, Ruwan Duminda, Rimal, Jyotsna, Kerr, Alexander Ross, Amtha, Rahmi, Patil, Karthikeya, Tilakaratne, Wanninayake Mudiyanselage, Gibson, John, Cheong, Sok Ching & Barman, Sarah Ann (2020). Automated Detection and Classification of Oral Lesions Using Deep Learning for Early Detection of Oral Cancer. IEEE ACCESS 8: 132677-132693.
• Saeed, R. A., Recupero, Diego Reforgiato & Remagnino, Paolo (2020). A Boundary Node Method for path planning of mobile robots. ROBOTICS AND AUTONOMOUS SYSTEMS 123: 103320.
• Lee, Sue Han, Chan, Chee Seng & Remagnino, Paolo (2018). Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks. IEEE TRANSACTIONS ON IMAGE PROCESSING 27(9): 4287-4301.
• Lee, Sue Han, Chan, Chee Seng, Mayo, Simon Joseph & Remagnino, Paolo (2017). How deep learning extracts and learns leaf features for plant classification. PATTERN RECOGNITION 71: 1-13.
• Cope, J. S., Remagnino, P., Mannan, S., Diaz, K., Ferri, F. J. & Wilkin, P. (2013). Reverse engineering expert visual observations: From fixations to the learning of spatial filters with a neural-gas algorithm. EXPERT SYSTEMS WITH APPLICATIONS 40(17): 6707-6712.
• Thida, Myo, Eng, How-Lung & Remagnino, Paolo (2013). Laplacian Eigenmap With Temporal Constraints for Local Abnormality Detection in Crowded Scenes. IEEE TRANSACTIONS ON CYBERNETICS 43(6): 2147-2156.
• Fraz, M. M., Remagnino, P., Hoppe, A., Rudnicka, A. R., Owen, C. G., Whincup, P. H. & Barman, S. A. (2013). Quantification of blood vessel calibre in retinal images of multi-ethnic school children using a model based approach. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 37(1): 48-60.
• Fraz, Muhammad Moazam, Remagnino, Paolo, Hoppe, Andreas, Uyyanonvara, Bunyarit, Rudnicka, Alicja R., Owen, Christopher G. & Barman, Sarah A. (2012). An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 59(9): 2538-2548.
• Fraz, M. M., Barman, S. A., Remagnino, P., Hoppe, A., Basit, A., Uyyanonvara, B., Rudnicka, A. R. & Owen, C. G. (2012). An approach to localize the retinal blood vessels using bit planes and centerline detection. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 108(2): 600-616.
• Fraz, M. M., Remagnino, P., Hoppe, A., Uyyanonvara, B., Rudnicka, A. R., Owen, C. G. & Barman, S. A. (2012). Blood vessel segmentation methodologies in retinal images - A survey. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 108(1): 407-433.