Zobrazeno 1 - 10
of 132
pro vyhledávání: '"Vessio, Gennaro"'
Precision agriculture relies heavily on effective weed management to ensure robust crop yields. This study presents RoWeeder, an innovative framework for unsupervised weed mapping that combines crop-row detection with a noise-resilient deep learning
Externí odkaz:
http://arxiv.org/abs/2410.04983
Artificial Intelligence and generative models have revolutionized music creation, with many models leveraging textual or visual prompts for guidance. However, existing image-to-music models are limited to simple images, lacking the capability to gene
Externí odkaz:
http://arxiv.org/abs/2410.04906
Autor:
Loconte, Lorenzo, Mari, Antonio, Gala, Gennaro, Peharz, Robert, de Campos, Cassio, Quaeghebeur, Erik, Vessio, Gennaro, Vergari, Antonio
This paper establishes a rigorous connection between circuit representations and tensor factorizations, two seemingly distinct yet fundamentally related areas. By connecting these fields, we highlight a series of opportunities that can benefit both c
Externí odkaz:
http://arxiv.org/abs/2409.07953
Autor:
De Marinis, Pasquale, Fanelli, Nicola, Scaringi, Raffaele, Colonna, Emanuele, Fiameni, Giuseppe, Vessio, Gennaro, Castellano, Giovanna
We present Label Anything, an innovative neural network architecture designed for few-shot semantic segmentation (FSS) that demonstrates remarkable generalizability across multiple classes with minimal examples required per class. Diverging from trad
Externí odkaz:
http://arxiv.org/abs/2407.02075
Publikováno v:
Pattern Recognition Letters, vol. 128, pp. 204-210 (2019)
Computer aided diagnosis systems can provide non-invasive, low-cost tools to support clinicians. These systems have the potential to assist the diagnosis and monitoring of neurodegenerative disorders, in particular Parkinson's disease (PD). Handwriti
Externí odkaz:
http://arxiv.org/abs/2405.13438
Publikováno v:
Neural Computing and Applications, Volume 36, pages 2411 to 2427 (2024)
Signature verification is a critical task in many applications, including forensic science, legal judgments, and financial markets. However, current signature verification systems are often difficult to explain, which can limit their acceptance in th
Externí odkaz:
http://arxiv.org/abs/2405.12695
Publikováno v:
Neurocomputing (2023)
Crowd analysis from drones has attracted increasing attention in recent times due to the ease of use and affordable cost of these devices. However, how this technology can provide a solution to crowd flow detection is still an unexplored research que
Externí odkaz:
http://arxiv.org/abs/2301.04937
Autor:
Du, Dawei, Wen, Longyin, Zhu, Pengfei, Fan, Heng, Hu, Qinghua, Ling, Haibin, Shah, Mubarak, Pan, Junwen, Al-Ali, Ali, Mohamed, Amr, Imene, Bakour, Dong, Bin, Zhang, Binyu, Nesma, Bouchali Hadia, Xu, Chenfeng, Duan, Chenzhen, Castiello, Ciro, Mencar, Corrado, Liang, Dingkang, Krüger, Florian, Vessio, Gennaro, Castellano, Giovanna, Wang, Jieru, Gao, Junyu, Abualsaud, Khalid, Ding, Laihui, Zhao, Lei, Cianciotta, Marco, Saqib, Muhammad, Almaadeed, Noor, Elharrouss, Omar, Lyu, Pei, Wang, Qi, Liu, Shidong, Qiu, Shuang, Pan, Siyang, Al-Maadeed, Somaya, Khan, Sultan Daud, Khattab, Tamer, Han, Tao, Golda, Thomas, Xu, Wei, Bai, Xiang, Xu, Xiaoqing, Li, Xuelong, Zhao, Yanyun, Tian, Ye, Lin, Yingnan, Xu, Yongchao, Yao, Yuehan, Xu, Zhenyu, Zhao, Zhijian, Luo, Zhipeng, Wei, Zhiwei, Zhao, Zhiyuan
Publikováno v:
European Conference on Computer Vision. Springer, Cham, 2020: 675-691
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algorithms focusing on crowd counting on the dr
Externí odkaz:
http://arxiv.org/abs/2107.08766
Autor:
Castellano, Giovanna, Vessio, Gennaro
Clustering artworks is difficult for several reasons. On the one hand, recognizing meaningful patterns based on domain knowledge and visual perception is extremely hard. On the other hand, applying traditional clustering and feature reduction techniq
Externí odkaz:
http://arxiv.org/abs/2106.06234
Automatic art analysis has seen an ever-increasing interest from the pattern recognition and computer vision community. However, most of the current work is mainly based solely on digitized artwork images, sometimes supplemented with some metadata an
Externí odkaz:
http://arxiv.org/abs/2105.15028