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ORCIDNicola Strisciuglio
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- affiliation: University of Groningen, The Netherlands
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2020 – today
- 2025
[j22]Alessandro Bruno, Pier Luigi Mazzeo, Nicola Strisciuglio, Barbara Hammer, Mingliang Gao:
Editorial: Computer vision and AI in real-world applications: robustness, generalization, and engineering. Frontiers Comput. Sci. 7 (2025)- [c33]Boqian Wu, Qiao Xiao, Shunxin Wang, Nicola Strisciuglio, Mykola Pechenizkiy, Maurice van Keulen, Decebal Constantin Mocanu, Elena Mocanu:
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness. ICLR 2025 - [i29]Shunxin Wang, Raymond N. J. Veldhuis, Nicola Strisciuglio:
Do ImageNet-trained models learn shortcuts? The impact of frequency shortcuts on generalization. CoRR abs/2503.03519 (2025) - [i28]Davide Berasi, Matteo Farina, Massimiliano Mancini, Elisa Ricci, Nicola Strisciuglio:
Not Only Text: Exploring Compositionality of Visual Representations in Vision-Language Models. CoRR abs/2503.17142 (2025) - 2024
- [j21]Virginia Riego-Del Castillo, Lidia Sánchez-González
, Nicola Strisciuglio:
Optimized network for detecting burr-breakage in images of milling workpieces. Log. J. IGPL 32(4): 624-633 (2024) - [j20]Adjorn van Engelenhoven, Nicola Strisciuglio, Estefanía Talavera:
CAST: Clustering self-Attention using Surrogate Tokens for efficient transformers. Pattern Recognit. Lett. 186: 30-36 (2024) - [j19]Sven Dummer, Nicola Strisciuglio, Christoph Brune:
RDA-INR: Riemannian Diffeomorphic Autoencoding via Implicit Neural Representations. SIAM J. Imaging Sci. 17(4): 2302-2330 (2024) - [j18]Zohra Rezgui, Nicola Strisciuglio, Raymond N. J. Veldhuis:
Gender Privacy Angular Constraints for Face Recognition. IEEE Trans. Biom. Behav. Identity Sci. 6(3): 352-363 (2024) - [c32]Marissa Jonker, Wesley Roozing, Nicola Strisciuglio:
Synthetic Data-Based Training of Instance Segmentation: A Robotic Bin-Picking Pipeline for Chicken Fillets. CASE 2024: 2805-2812 - [c31]Puru Vaish, Shunxin Wang, Nicola Strisciuglio:
Fourier-Basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification. CVPR 2024: 17763-17772 - [c30]Zohra Rezgui, Nicola Strisciuglio, Raymond N. J. Veldhuis:
Controllable Privacy in Face Recognition: A Filter-based Approach. IJCB 2024: 1-9 - [c29]Guru Swaroop Bennabhaktula, Enrique Alegre, Nicola Strisciuglio, George Azzopardi:
PushPull-Net: Inhibition-Driven ResNet Robust to Image Corruptions. ICPR (8) 2024: 391-408 - [c28]Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Regressing Transformers for Data-efficient Visual Place Recognition. ICRA 2024: 15898-15904 - [c27]Pablo Laso, Stefano Cerri, Annabel Sorby-Adams, Jennifer Guo, Farrah Mateen, Philipp Goebl, Jiaming Wu, Peirong Liu, Hongwei Bran Li, Sean I. Young, Benjamin Billot, Oula Puonti, Gordon Sze, Sam Payabavash, Adam DeHavenon, Kevin N. Sheth, Matthew S. Rosen, John Kirsch, Nicola Strisciuglio, Jelmer M. Wolterink, Arman Eshaghi, Frederik Barkhof, W. Taylor Kimberly, Juan Eugenio Iglesias:
Quantifying White Matter Hyperintensity and Brain Volumes in Heterogeneous Clinical and Low-Field Portable MRI. ISBI 2024: 1-5 - [c26]Zohra Rezgui, Nicola Strisciuglio, Raymond N. J. Veldhuis:
Enhancing Soft Biometric Face Template Privacy with Mutual Information-Based Image Attacks. WACV (Workshops) 2024: 1141-1149 - [i27]Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Regressing Transformers for Data-efficient Visual Place Recognition. CoRR abs/2401.16304 (2024) - [i26]Adjorn van Engelenhoven, Nicola Strisciuglio, Estefanía Talavera:
CAST: Clustering Self-Attention using Surrogate Tokens for Efficient Transformers. CoRR abs/2402.04239 (2024) - [i25]Puru Vaish, Shunxin Wang, Nicola Strisciuglio:
Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification. CoRR abs/2403.01944 (2024) - [i24]Guru Swaroop Bennabhaktula, Enrique Alegre, Nicola Strisciuglio, George Azzopardi:
PushPull-Net: Inhibition-driven ResNet robust to image corruptions. CoRR abs/2408.04077 (2024) - [i23]Willams de Lima Costa, Raul Ismayilov, Nicola Strisciuglio, Estefania Talavera Martínez:
Indoor scene recognition from images under visual corruptions. CoRR abs/2408.13029 (2024) - [i22]Boqian Wu, Qiao Xiao, Shunxin Wang, Nicola Strisciuglio, Mykola Pechenizkiy, Maurice van Keulen, Decebal Constantin Mocanu, Elena Mocanu:
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness. CoRR abs/2410.03030 (2024) - 2023
- [j17]Antonio Greco, Nicola Strisciuglio, Mario Vento, Vincenzo Vigilante:
Benchmarking deep networks for facial emotion recognition in the wild. Multim. Tools Appl. 82(8): 11189-11220 (2023) - [c25]Ioana Mazilu, Shunxin Wang, Sven Dummer, Raymond N. J. Veldhuis, Christoph Brune, Nicola Strisciuglio:
Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space. CAIP (2) 2023: 201-211 - [c24]Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Data-Efficient Large Scale Place Recognition with Graded Similarity Supervision. CVPR 2023: 23487-23496 - [c23]Shunxin Wang, Raymond N. J. Veldhuis, Christoph Brune, Nicola Strisciuglio:
What do neural networks learn in image classification? A frequency shortcut perspective. ICCV 2023: 1433-1442 - [c22]Shunxin Wang, Christoph Brune, Raymond N. J. Veldhuis, Nicola Strisciuglio:
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning. ICCV (Workshops) 2023: 129-138 - [i21]Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Data-efficient Large Scale Place Recognition with Graded Similarity Supervision. CoRR abs/2303.11739 (2023) - [i20]Shunxin Wang, Raymond N. J. Veldhuis, Nicola Strisciuglio:
The Robustness of Computer Vision Models against Common Corruptions: a Survey. CoRR abs/2305.06024 (2023) - [i19]Sven Dummer, Nicola Strisciuglio, Christoph Brune:
RSA-INR: Riemannian Shape Autoencoding via 4D Implicit Neural Representations. CoRR abs/2305.12854 (2023) - [i18]Shunxin Wang, Raymond N. J. Veldhuis, Christoph Brune, Nicola Strisciuglio:
What do neural networks learn in image classification? A frequency shortcut perspective. CoRR abs/2307.09829 (2023) - [i17]Ioana Mazilu, Shunxin Wang, Sven Dummer, Raymond N. J. Veldhuis, Christoph Brune, Nicola Strisciuglio:
Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space. CoRR abs/2307.15461 (2023) - [i16]Shunxin Wang, Christoph Brune, Raymond N. J. Veldhuis, Nicola Strisciuglio:
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning. CoRR abs/2308.06622 (2023) - [i15]Pablo Laso, Stefano Cerri, Annabel Sorby-Adams, Jennifer Guo, Farrah Mateen, Philipp Goebl, Jiaming Wu, Peirong Liu, Hongwei Li, Sean I. Young, Benjamin Billot, Oula Puonti, Gordon Sze, Sam Payabavash, Adam DeHavenon, Kevin N. Sheth, Matthew S. Rosen, John Kirsch, Nicola Strisciuglio, Jelmer M. Wolterink, Arman Eshaghi, Frederik Barkhof, W. Taylor Kimberly, Juan Eugenio Iglesias:
Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI. CoRR abs/2312.05119 (2023) - 2022
- [j16]Virginia Riego-Del Castillo, Lidia Sánchez-González, Adrián Campazas Vega, Nicola Strisciuglio:
Vision-Based Module for Herding with a Sheepdog Robot. Sensors 22(14): 5321 (2022) - [c21]Vaidehi Pandey, Christoph Brune, Nicola Strisciuglio:
Self-supervised Learning Through Colorization for Microscopy Images. ICIAP (2) 2022: 621-632 - [i14]Stefan Haller, Adina Aldea, Christin Seifert, Nicola Strisciuglio:
Survey on Automated Short Answer Grading with Deep Learning: from Word Embeddings to Transformers. CoRR abs/2204.03503 (2022) - 2021
- [j15]Virginia Riego, Lidia Sánchez-González, Laura Fernández-Robles, Alexis Gutiérrez-Fernández, Nicola Strisciuglio:
Burr detection and classification using RUSTICO and image processing. J. Comput. Sci. 56: 101485 (2021) - [c20]Rafaël Brandt, Nicola Strisciuglio, Nicolai Petkov:
MTStereo 2.0: Accurate Stereo Depth Estimation via Max-Tree Matching. CAIP (1) 2021: 110-119 - [c19]Akul Mehra, Luuk J. Spreeuwers, Nicola Strisciuglio:
Deepfake Detection using Capsule Networks and Long Short-Term Memory Networks. VISIGRAPP (4: VISAPP) 2021: 407-414 - [i13]Nicola Strisciuglio:
Brain-inspired algorithms for processing of visual data. CoRR abs/2103.01634 (2021) - [i12]Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Generalized Contrastive Optimization of Siamese Networks for Place Recognition. CoRR abs/2103.06638 (2021) - 2020
- [j14]Rubén Álvarez, Javier Díez-González, Nicola Strisciuglio, Hilde Pérez:
Multi-Objective Optimization for Asynchronous Positioning Systems Based on a Complete Characterization of Ranging Errors in 3D Complex Environments. IEEE Access 8: 43046-43056 (2020) - [j13]Damiano Melotti, Kevin Heimbach, Antonio Jose Rodríguez-Sánchez, Nicola Strisciuglio, George Azzopardi:
A robust contour detection operator with combined push-pull inhibition and surround suppression. Inf. Sci. 524: 229-240 (2020) - [j12]Sivakumar Ramachandran, Nicola Strisciuglio, Anand Vinekar, Renu John, George Azzopardi:
U-COSFIRE filters for vessel tortuosity quantification with application to automated diagnosis of retinopathy of prematurity. Neural Comput. Appl. 32(16): 12453-12468 (2020) - [j11]Nicola Strisciuglio, Manuel Lopez-Antequera, Nicolai Petkov:
Enhanced robustness of convolutional networks with a push-pull inhibition layer. Neural Comput. Appl. 32(24): 17957-17971 (2020) - [j10]Rafaël Brandt, Nicola Strisciuglio, Nicolai Petkov, Michael H. F. Wilkinson:
Efficient binocular stereo correspondence matching with 1-D Max-Trees. Pattern Recognit. Lett. 135: 402-408 (2020) - [e3]Nicolai Petkov, Nicola Strisciuglio, Carlos M. Travieso-González:
APPIS 2020: 3rd International Conference on Applications of Intelligent Systems, APPIS 2020, Las Palmas de Gran Canaria Spain, 7-9 January 2020. ACM 2020, ISBN 978-1-4503-7630-3 [contents] - [i11]Rafaël Brandt, Nicola Strisciuglio, Nicolai Petkov:
MTStereo 2.0: improved accuracy of stereo depth estimation withMax-trees. CoRR abs/2006.15373 (2020)
2010 – 2019
- 2019
- [j9]Maria Leyva-Vallina, Nicola Strisciuglio, Manuel Lopez-Antequera, Radim Tylecek, Michael Blaich, Nicolai Petkov:
TB-Places: A Data Set for Visual Place Recognition in Garden Environments. IEEE Access 7: 52277-52287 (2019) - [j8]Manuel Lopez-Antequera, Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Place and Object Recognition by CNN-Based COSFIRE Filters. IEEE Access 7: 66157-66166 (2019) - [j7]Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Learning representations of sound using trainable COPE feature extractors. Pattern Recognit. 92: 25-36 (2019) - [j6]Alessia Saggese, Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Learning skeleton representations for human action recognition. Pattern Recognit. Lett. 118: 23-31 (2019) - [j5]Nicola Strisciuglio, George Azzopardi, Nicolai Petkov:
Robust Inhibition-Augmented Operator for Delineation of Curvilinear Structures. IEEE Trans. Image Process. 28(12): 5852-5866 (2019) - [c18]Nicola Strisciuglio, Nicolai Petkov:
Brain-Inspired Algorithms for Processing of Visual Data. BrainComp 2019: 105-115 - [c17]Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Place Recognition in Gardens by Learning Visual Representations: Data Set and Benchmark Analysis. CAIP (1) 2019: 324-335 - [c16]Nicola Strisciuglio, Nicolai Petkov:
Trainable COPE Features for Sound Event Detection. CIARP 2019: 599-609 - [c15]Pasquale Foggia, Alessia Saggese, Nicola Strisciuglio, Mario Vento, Vincenzo Vigilante:
Detecting Sounds of Interest in Roads with Deep Networks. ICIAP (2) 2019: 583-592 - [e2]Nicolai Petkov, Nicola Strisciuglio, Carlos M. Travieso:
Proceedings of the 2nd International Conference on Applications of Intelligent Systems, APPIS 2019, Las Palmas de Gran Canaria, Spain, January 07-09, 2019. ACM 2019, ISBN 978-1-4503-6085-2 [contents] - [i10]Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Learning sound representations using trainable COPE feature extractors. CoRR abs/1901.06904 (2019) - [i9]Nicola Strisciuglio, Manuel Lopez-Antequera, Nicolai Petkov:
A Push-Pull Layer Improves Robustness of Convolutional Neural Networks. CoRR abs/1901.10208 (2019) - [i8]Maria Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov:
Place recognition in gardens by learning visual representations: data set and benchmark analysis. CoRR abs/1906.12151 (2019) - 2018
- [c14]Juan Buhagiar, Nicola Strisciuglio, Nicolai Petkov, George Azzopardi:
Automatic Segmentation of Indoor and Outdoor Scenes from Visual Lifelogging. APPIS 2018: 194-202 - [c13]Nicola Strisciuglio, George Azzopardi, Nicolai Petkov:
Brain-Inspired Robust Delineation Operator. ECCV Workshops (3) 2018: 555-565 - [c12]Nicola Strisciuglio, Maria Leyva-Vallina, Nicolai Petkov, Rafael Muñoz-Salinas:
Camera Localization in Outdoor Garden Environments Using Artificial Landmarks. IWOBI 2018: 1-6 - [e1]Nicolai Petkov, Nicola Strisciuglio, Carlos Manuel Travieso-González:
Applications of Intelligent Systems - Proceedings of the 1st International APPIS Conference 2018, Las Palmas de Gran Canaria, Spain, 8-12 January 2018. Frontiers in Artificial Intelligence and Applications 310, IOS Press 2018, ISBN 978-1-61499-928-7 [contents] - [i7]Nicola Strisciuglio:
Learning audio and image representations with bio-inspired trainable feature extractors. CoRR abs/1801.00688 (2018) - [i6]Nicola Strisciuglio, Radim Tylecek, Nicolai Petkov, Peter Bieber, Jochen Hemming, Eldert J. van Henten, Torsten Sattler, Marc Pollefeys, Theo Gevers, Thomas Brox, Robert B. Fisher:
TrimBot2020: an outdoor robot for automatic gardening. CoRR abs/1804.01792 (2018) - [i5]Nicola Strisciuglio, George Azzopardi, Nicolai Petkov:
Brain-inspired robust delineation operator. CoRR abs/1811.10240 (2018) - 2017
- [c11]Alessia Saggese, Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
A real-time system for audio source localization with cheap sensor device. AVSS 2017: 1-7 - [c10]Nicola Strisciuglio, George Azzopardi, Nicolai Petkov:
Detection of Curved Lines with B-COSFIRE Filters: A Case Study on Crack Delineation. CAIP (1) 2017: 108-120 - [c9]Estefanía Talavera, Nicola Strisciuglio, Nicolai Petkov, Petia Radeva:
Sentiment Recognition in Egocentric Photostreams. IbPRIA 2017: 471-479 - [c8]Nicola Strisciuglio, Nicolai Petkov:
Delineation of line patterns in images using B-COSFIRE filters. IWOBI 2017: 1-6 - [i4]Estefanía Talavera, Nicola Strisciuglio, Nicolai Petkov, Petia Radeva:
Sentiment Recognition in Egocentric Photostreams. CoRR abs/1703.09933 (2017) - [i3]Nicola Strisciuglio, Nicolai Petkov:
Delineation of line patterns in images using B-COSFIRE filters. CoRR abs/1707.07438 (2017) - [i2]Nicola Strisciuglio, George Azzopardi, Nicolai Petkov:
Detection of curved lines with B-COSFIRE filters: A case study on crack delineation. CoRR abs/1707.07747 (2017) - [i1]Alessia Saggese, Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Action recognition by learning pose representations. CoRR abs/1708.00672 (2017) - 2016
- [j4]Nicola Strisciuglio, George Azzopardi, Mario Vento, Nicolai Petkov:
Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters. Mach. Vis. Appl. 27(8): 1137-1149 (2016) - [j3]Pasquale Foggia, Nicolai Petkov, Alessia Saggese, Nicola Strisciuglio, Mario Vento:
Audio Surveillance of Roads: A System for Detecting Anomalous Sounds. IEEE Trans. Intell. Transp. Syst. 17(1): 279-288 (2016) - [c7]Alessia Saggese, Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Time-frequency analysis for audio event detection in real scenarios. AVSS 2016: 438-443 - 2015
- [j2]George Azzopardi, Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Trainable COSFIRE filters for vessel delineation with application to retinal images. Medical Image Anal. 19(1): 46-57 (2015) - [j1]Pasquale Foggia, Nicolai Petkov, Alessia Saggese, Nicola Strisciuglio, Mario Vento:
Reliable detection of audio events in highly noisy environments. Pattern Recognit. Lett. 65: 22-28 (2015) - [c6]Pasquale Foggia, Alessia Saggese, Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Car crashes detection by audio analysis in crowded roads. AVSS 2015: 1-6 - [c5]Nicola Strisciuglio, Mario Vento, Nicolai Petkov:
Bio-Inspired Filters for Audio Analysis. BrainComp 2015: 101-115 - [c4]Nicola Strisciuglio, George Azzopardi, Mario Vento, Nicolai Petkov:
Multiscale Blood Vessel Delineation Using B-COSFIRE Filters. CAIP (2) 2015: 300-312 - 2014
- [c3]Pasquale Foggia, Alessia Saggese, Nicola Strisciuglio, Mario Vento:
Cascade classifiers trained on gammatonegrams for reliably detecting audio events. AVSS 2014: 50-55 - [c2]Pasquale Foggia, Alessia Saggese, Nicola Strisciuglio, Mario Vento:
Exploiting the deep learning paradigm for recognizing human actions. AVSS 2014: 93-98 - 2013
- [c1]Vincenzo Carletti, Pasquale Foggia, Gennaro Percannella, Alessia Saggese, Nicola Strisciuglio, Mario Vento:
Audio surveillance using a bag of aural words classifier. AVSS 2013: 81-86
Coauthor Index
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