Results 21 to 30 of about 849,090 (345)
An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression
Sensors, 2023 Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual ...
Guoliang Luo +6 more
doaj +1 more source
Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods [PDF]
, 2018 This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises ...
Arcos García, Álvaro +2 more
core +1 more source
Content-aware convolutional neural networks [PDF]
Neural Networks, 2021 Accepted by Neural ...
Mingkui Tan +7 more
openaire +4 more sources
Optimization design of binary VGG convolutional neural network accelerator
Dianzi Jishu Yingyong, 2021 Most of the existing researches on accelerators of binary convolutional neural networks based on FPGA are aimed at small-scale image input, while the applications mainly take large-scale convolutional neural networks such as YOLO and VGG as backbone ...
Zhang Xuxin +3 more
doaj +1 more source
Detection of exomoons in simulated light curves with a regularized convolutional neural network
, 2020 Many moons have been detected around planets in our Solar System, but none has been detected unambiguously around any of the confirmed extrasolar planets.
Alshehhi, Rasha +3 more
core +1 more source
Image Denoising with Graph-Convolutional Neural Networks [PDF]
, 2019 Recovering an image from a noisy observation is a key problem in signal processing. Recently, it has been shown that data-driven approaches employing convolutional neural networks can outperform classical model-based techniques, because they can capture ...
Fracastoro, Giulia +2 more
core +2 more sources
Hyper-Convolution Networks for Biomedical Image Segmentation [PDF]
, 2021 The convolution operation is a central building block of neural network architectures widely used in computer vision. The size of the convolution kernels determines both the expressiveness of convolutional neural networks (CNN), as well as the number of learnable parameters.
arxiv +1 more source
Convolutional Neural Networks With Dynamic Regularization [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Regularization is commonly used for alleviating overfitting in machine learning. For convolutional neural networks (CNNs), regularization methods, such as DropBlock and Shake-Shake, have illustrated the improvement in the generalization performance. However, these methods lack a self-adaptive ability throughout training.
Yi Wang +3 more
openaire +4 more sources
Advanced Materials Interfaces, EarlyView., 2023 This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi +4 more
wiley +1 more source
Diagnostics, 2022 Background: Otitis media includes several common inflammatory conditions of the middle ear that can have severe complications if left untreated. Correctly identifying otitis media can be difficult and a screening system supported by machine learning ...
Josefin Sandström +4 more
doaj +1 more source