Results 21 to 30 of about 595,263 (265)

Generalization in Deep Learning

, 2022
Published by Cambridge University Press.
Kawaguchi, Kenji, Bengio, Yoshua, Kaelbling, Leslie Pak   +2 more
openaire   +3 more sources

Deep learning

American Journal of Orthodontics and Dentofacial Orthopedics
Flemish Government under the "Onder-zoeksprogramma ...
Axel-Jan Rousseau, Melvin Geubbelmans, Tomasz Burzykowski, Dirk Valkenborg   +3 more
openaire   +3 more sources

Prediction for Manufacturing Factors in a Steel Plate Rolling Smart Factory Using Data Clustering-Based Machine Learning

IEEE Access, 2020
A Steel Plate Rolling Mill (SPM) is a milling machine that uses rollers to press hot slab inputs to produce ferrous or non-ferrous metal plates. To produce high-quality steel plates, it is important to precisely detect and sense values of manufacturing ...
Cheol Young Park, Jin Woog Kim, Bosung Kim, Joongyoon Lee   +3 more
doaj   +1 more source

Deep learning microscopy

Optica, 2017
We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design.
Yair Rivenson, Zoltán Göröcs, Harun Günaydin, Yibo Zhang, Hongda Wang, Aydogan Ozcan   +5 more
openaire   +4 more sources

Deep Learning in Medicine

JACC: Advances, 2022
[Figure: see text]
Toma, Augustin, Diller, Gerhard-Paul, Lawler, Patrick R.   +2 more
openaire   +2 more sources

MAPE-K Recovery for Multimodal Robotic Navigation Under Sensor Anomalies

IEEE Access
Deep reinforcement learning (DRL) policies for robotic navigation can degrade when deployed sensors exhibit persistent anomalies that were not represented during nominal training.
Pavlos Tosidis, Nikolaos Passalis, Anastasios Tefas   +2 more
doaj   +1 more source

Causal Deep Learning

CoRR, 2023
Causality has the potential to truly transform the way we solve a large number of real-world problems. Yet, so far, its potential largely remains to be unlocked as causality often requires crucial assumptions which cannot be tested in practice. To address this challenge, we propose a new way of thinking about causality -- we call this causal deep ...
Jeroen Berrevoets, Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar   +3 more
openaire   +3 more sources

Inequality in breast cancer: Global statistics from 2022 to 2050

Breast
This study evaluates the global inequalities of breast cancer incidence and mortality from 2022 to 2050 with the latest GLOBOCAN estimates. It focuses on disparities across continents, age groups and Human Development Index (HDI) levels.
Ling Liao
doaj   +1 more source

Correction to: Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning

BMC Medical Informatics and Decision Making, 2019
Following publication of the original ...
Muhammad Naseer Bajwa, Muhammad Imran Malik, Shoaib Ahmed Siddiqui, Andreas Dengel, Faisal Shafait, Wolfgang Neumeier, Sheraz Ahmed   +6 more
doaj   +1 more source

Generalizable and efficient cross‐domain person re‐identification model using deep metric learning

IET Computer Vision, 2023
Most of the successful person re‐ID models conduct supervised training and need a large number of training data. These models fail to generalise well on unseen unlabelled testing sets.
Saba Sadat Faghih Imani, Kazim Fouladi‐Ghaleh, Hossein Aghababa   +2 more
doaj   +1 more source