Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Marco Zullich"'
Publikováno v:
IEEE Access, Vol 11, Pp 5864-5883 (2023)
In Late-Medieval panel paintings from the Tuscan area, mechanical tools called punches were used to impress repeated motifs on gold foils to create decorative patterns. Such patterns can be used as clues to objectively support the attribution of the
Externí odkaz:
https://doaj.org/article/79e4c8d81c81426d836d92e93f8e68b3
Autor:
Giorgia Nadizar, Eric Medvet, Ola Huse Ramstad, Stefano Nichele, Felice Andrea Pellegrino, Marco Zullich
Publikováno v:
The Knowledge Engineering Review. 37
Merging pruning and neuroevolution: towards robust and efficient controllers for modular soft robots
Autor:
Giorgia Nadizar, Eric Medvet, Hola Huse Ramstad, Stefano Nichele, Felice Andrea Pellegrino, Marco Zullich
Publikováno v:
Knowledge engineering review
e3
e3
Artificial neural networks (ANNs) can be employed as controllers for robotic agents. Their structure is often complex, with many neurons and connections, especially when the robots have many sensors and actuators distributed across their bodies and/o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd9789536a36828452d38aec674f62e6
https://hdl.handle.net/11250/3040433
https://hdl.handle.net/11250/3040433
Autor:
Benedetta Liberatori, Ciro Antonio Mami, Giovanni Santacatterina, Marco Zullich, Felice Andrea Pellegrino
Deploying Deep Learning (DL) based object detection (OD) models in low-end devices, such as single board computers, may lead to poor performance in terms of frames-per-second (FPS). Pruning and quantization are well-known compression techniques that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::195933916f31e3c13773b493796f032c
http://hdl.handle.net/11368/3028994
http://hdl.handle.net/11368/3028994
Publikováno v:
GECCO Companion
Artificial neural networks (ANNs) are commonly used for controlling robotic agents. For robots with many sensors and actuators, ANNs can be very complex, with many neurons and connections. Removal of neurons or connections, i.e., pruning, may be desi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50e5179f89652466d3ffe695c6482c04
http://hdl.handle.net/11368/2993384
http://hdl.handle.net/11368/2993384
Publikováno v:
ICPR
In recent years, Artificial Neural Networks (ANNs) pruning has become the focal point of many researches, due to the extreme overparametrization of such models. This has urged the scientific world to investigate methods for the simplification of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dbbd21435cbe1ec79da5029efdfa7cf2
http://hdl.handle.net/11368/2990454
http://hdl.handle.net/11368/2990454
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030661243
ICPRAM (Revised Selected Papers)
ICPRAM (Revised Selected Papers)
Deep Neural Networks (DNNs) are essential tools of modern science and technology. The current lack of explainability of their inner workings and of principled ways to tame their architectural complexity triggered a lot of research in recent years. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b8db4ed4d66ca74e02cac3e99ff28c6
http://hdl.handle.net/11368/2976859
http://hdl.handle.net/11368/2976859
Publikováno v:
Scopus-Elsevier
ICPRAM
ICPRAM
During the last few decades, artificial neural networks (ANN) have achieved an enormous success in regression and classification tasks. The empirical success has not been matched with an equally strong theoretical understanding of such models, as som
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb2474e671c9df6e0181d246e1b7ac75
http://www.scopus.com/inward/record.url?eid=2-s2.0-85082998374&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85082998374&partnerID=MN8TOARS