Results 21 to 30 of about 2,238,851 (367)
A modified Adam algorithm for deep neural network optimization
Neural computing & applications (Print), 2023 Deep Neural Networks (DNNs) are widely regarded as the most effective learning tool for dealing with large datasets, and they have been successfully used in thousands of applications in a variety of fields. Based on these large datasets, they are trained
M. Reyad, A. Sarhan, M. Arafa
semanticscholar +1 more source
Aggregated Residual Transformations for Deep Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2016 We present a simple, highly modularized network architecture for image classification. Our network is constructed by repeating a building block that aggregates a set of transformations with the same topology.
Saining Xie +4 more
semanticscholar +1 more source
A Novel Deep Neural Network Topology for Parametric Modeling of Passive Microwave Components
IEEE Access, 2020 Artificial neural network technique has gained recognition as a powerful technique in microwave modeling and design. This paper proposes a novel deep neural network topology for parametric modeling of microwave components.
Jing Jin +5 more
doaj +1 more source
Spiking Neural Network Based on Multi-Scale Saliency Fusion for Breast Cancer Detection
Entropy, 2022 Deep neural networks have been successfully applied in the field of image recognition and object detection, and the recognition results are close to or even superior to those from human beings.
Qiang Fu, Hongbin Dong
doaj +1 more source
A Model-Driven Deep Neural Network for Single Image Rain Removal [PDF]
Computer Vision and Pattern Recognition, 2020 Deep learning (DL) methods have achieved state-of-the-art performance in the task of single image rain removal. Most of current DL architectures, however, are still lack of sufficient interpretability and not fully integrated with physical structures ...
Hong Wang, Qi Xie, Qian Zhao, Deyu Meng
semanticscholar +1 more source
Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring [PDF]
Computer Vision and Pattern Recognition, 2016 Non-uniform blind deblurring for general dynamic scenes is a challenging computer vision problem as blurs arise not only from multiple object motions but also from camera shake, scene depth variation.
Seungjun Nah +2 more
semanticscholar +1 more source
Burst Pressure Prediction of API 5L X-Grade Dented Pipelines Using Deep Neural Network
Journal of Marine Science and Engineering, 2020 Mechanical damage is recognized as a problem that reduces the performance of oil and gas pipelines and has been the subject of continuous research. The artificial neural network in the spotlight recently is expected to be another solution to solve the ...
Dohan Oh +3 more
doaj +1 more source
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network [PDF]
BMC Medical Research Methodology, 2016 BackgroundMedical practitioners use survival models to explore and understand the relationships between patients’ covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear
Jared Katzman +5 more
semanticscholar +1 more source
Evolving Deep Neural Networks [PDF]
, 2019 The success of deep learning depends on finding an architecture to fit the task. As deep learning has scaled up to more challenging tasks, the architectures have become difficult to design by hand. This paper proposes an automated method, CoDeepNEAT, for optimizing deep learning architectures through evolution.
Olivier Francon +10 more
openaire +3 more sources
Deep Convolutional Neural Network for Inverse Problems in Imaging [PDF]
IEEE Transactions on Image Processing, 2016 In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades.
Kyong Hwan Jin +3 more
semanticscholar +1 more source