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Flavio Piccoli
Researcher at University of Milano-Bicocca
Publications - 19
Citations - 478
Flavio Piccoli is an academic researcher from University of Milano-Bicocca. The author has contributed to research in topics: Convolutional neural network & Computer science. The author has an hindex of 7, co-authored 12 publications receiving 249 citations. Previous affiliations of Flavio Piccoli include ETH Zurich & Politehnica University of Timișoara.
Papers
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Journal ArticleDOI
Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity.
TL;DR: A region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity, which outperforms the state of the art.
Journal ArticleDOI
Artistic photo filter removal using convolutional neural networks
TL;DR: The method uses a convolutional neural network for the prediction of the coefficients of local polynomial transformations that are applied to the input image and shows that the quality of the restoration performed by the method is clearly superior to that of traditional color balancing and restoration procedures.
Proceedings ArticleDOI
NTIRE 2019 Challenge on Image Enhancement: Methods and Results
Andrey Ignatov,Radu Timofte,Xiaochao Qu,Xingguang Zhou,Ting Liu,Pengfei Wan,Syed Waqas Zamir,Aditya Arora,Salman Khan,Fahad Shahbaz Khan,Ling Shao,Dongwon Park,Se Young Chun,Pablo Navarrete Michelini,Hanwen Liu,Dan Zhu,Zhiwei Zhong,Xianming Liu,Junjun Jiang,Debin Zhao,Muhammad Haris,Kazutoshi Akita,Tomoki Yoshida,Greg Shakhnarovich,Norimichi Ukita,Jie Liu,Cheolkon Jung,Raimondo Schettini,Simone Bianco,Claudio Cusano,Flavio Piccoli,Pengju Liu,Kai Zhang,Jingdong Liu,Jiye Liu,Hongzhi Zhang,Wangmeng Zuo,Nelson Chong Ngee Bow,Lai-Kuan Wong,John See,Jinghui Qin,Lishan Huang,Yukai Shi,Pengxu Wei,Wushao Wen,Liang Lin,Zheng Hui,Xiumei Wang,Xinbo Gao,Kanti Kumari,Vikas Kumar Anand,Mahendra Khened,Ganapathy Krishnamurthi +52 more
TL;DR: The first NTIRE challenge on perceptual image enhancement as discussed by the authors focused on proposed solutions and results of real-world photo enhancement problem, where the goal was to map low-quality photos from the iPhone 3GS device to the same photos captured with Canon 70D DSLR camera.
Proceedings ArticleDOI
NTIRE 2019 Image Dehazing Challenge Report
Codruta O. Ancuti,Cosmin Ancuti,Radu Timofte,Luc Van Gool,Lei Zhang,Ming-Hsuan Yang,Tiantong Guo,Xuelu Li,Venkateswararao Cherukuri,Vishal Monga,Hao Jiang,Siyuan Yang,Yan Liu,Xiaochao Qu,Pengfei Wan,Dongwon Park,Se Young Chun,Ming Hong,Jinying Huang,Yizi Chen,Shuxin Chen,Bomin Wang,Pablo Navarrete Michelini,Hanwen Liu,Dan Zhu,Jing Liu,Sanchayan Santra,Ranjan Mondal,Bhabatosh Chanda,Peter Morales,Tzofi Klinghoffer,Le Manh Quan,Yong-Guk Kim,Xiao Liang,Runde Li,Jinshan Pan,Jinhui Tang,Kuldeep Purohit,Maitreya Suin,A. N. Rajagopalan,Raimondo Schettini,Simone Bianco,Flavio Piccoli,C. Cusano,Luigi Celona,Sunhee Hwang,Yu Seung Ma,Hyeran Byun,Subrahmanyam Murala,Akshay Dudhane,Harsh Aulakh,Tianxiang Zheng,Tao Zhang,Weining Qin,Runnan Zhou,Shanhu Wang,Jean-Philippe Tarel,Chuansheng Wang,Jiawei Wu +58 more
TL;DR: This paper reviews the second NTIRE challenge on image dehazing (restoration of rich details in hazy image) with focus on proposed solutions and results and gauge the state-of-the-art in imageDehazing.
Journal ArticleDOI
A Novel Approach to Data Augmentation for Pavement Distress Segmentation
TL;DR: It is shown how, starting from few labeled images, it is possible to augment small and long-tail datasets by producing new images with the associated semantic layouts and a remarkable increase in performance, especially with low cardinality classes, when CNNs are trained on the augmented datasets with respect to original datasets.