Results 141 to 150 of about 2,004,297 (387)

Training convolutional neural networks with megapixel images [PDF]

arXiv, 2018
To train deep convolutional neural networks, the input data and the intermediate activations need to be kept in memory to calculate the gradient descent step. Given the limited memory available in the current generation accelerator cards, this limits the maximum dimensions of the input data.
arxiv  

Convolutional Neural Networks: A Survey

Computers, 2023
Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of AI that have emerged as a powerful tool for various tasks including image recognition, speech recognition, natural language processing (NLP), and even in the field of ...
openaire   +2 more sources

Integration of Perovskite/Low‐Dimensional Material Heterostructures for Optoelectronics and Artificial Visual Systems

Advanced Functional Materials, EarlyView.
Heterojunctions combining halide perovskites with low‐dimensional materials enhance optoelectronic devices by enabling precise charge control and improving efficiency, stability, and speed. These synergies advance flexible electronics, wearable sensors, and neuromorphic computing, mimicking biological vision for real‐time image analysis and intelligent
Yu‐Jin Du, Junjie Yang, Ziyu Lv, Yongbiao Zhai, Zezhuang Yi, Yuhui Xie, Ming‐Lin Zheng, Xiangyu Ma, Guodong Gong, Yan Wang, Ye Zhou, Su‐Ting Han   +11 more
wiley   +1 more source

Bone tumor examination based on FCNN-4s and CRF fine segmentation fusion algorithm

Journal of Bone Oncology, 2023
Background and objective: Bone tumor is a kind of harmful orthopedic disease, there are benign and malignant points. Aiming at the problem that the accuracy of the existing machine learning algorithm for bone tumor image segmentation is not high, a bone ...
Shiqiang Wu, Xiaoming Bai, Liquan Cai, Liangming Wang, XiaoLu Zhang, Qingfeng Ke, Jianlong Huang   +6 more
doaj  

Laser‐Induced Graphene‐Assisted Patterning and Transfer of Silver Nanowires for Ultra‐Conformal Breathable Epidermal Electrodes in Long‐Term Electrophysiological Monitoring

Advanced Functional Materials, EarlyView.
This study presents a novel method using laser‐induced graphene (LIG) to enable high‐yield transfer of silver nanowire (AgNW) networks onto ultra‐low modulus, breathable silicone substrates. This approach creates ultra‐conformal epidermal electrodes (≈50 µm) for long‐term, high‐fidelity electrophysiological monitoring, even in challenging conditions ...
Jiuqiang Li, Senhao Zhang, Jun Zhong, Benkun Bao, Kai Guo, Yingying Zhang, Kerong Yang, Yao Tong, Donghai Qiu, Hongbo Yang, Huanyu Cheng   +10 more
wiley   +1 more source

Frequency-Domain and Spatial-Domain MLMVN-Based Convolutional Neural Networks

Algorithms
This paper presents a detailed analysis of a convolutional neural network based on multi-valued neurons (CNNMVN) and a fully connected multilayer neural network based on multi-valued neurons (MLMVN), employed here as a convolutional neural network in the
Igor Aizenberg, Alexander Vasko
doaj   +1 more source

Deep convolutional neural network based medical image classification for disease diagnosis

Journal of Big Data, 2019
Medical image classification plays an essential role in clinical treatment and teaching tasks. However, the traditional method has reached its ceiling on performance.
Samir S. Yadav, S. Jadhav
semanticscholar   +1 more source

Optoelectronic Devices for In‐Sensor Computing

Advanced Materials, EarlyView.
The raw data obtained directly from sensors in the noisy analogue domain is often unstructured, which lacks a predefined format or organization and does not conform to a specific data model. Optoelectronic devices for in‐sensor visual processing can integrate perception, memory, and processing functions in the same physical units, which can compress ...
Qinqi Ren, Chaoyi Zhu, Sijie Ma, Zhaoqing Wang, Jianmin Yan, Tianqing Wan, Weicheng Yan, Yang Chai   +7 more
wiley   +1 more source

4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks [PDF]

arXiv, 2019
In many robotics and VR/AR applications, 3D-videos are readily-available sources of input (a continuous sequence of depth images, or LIDAR scans). However, those 3D-videos are processed frame-by-frame either through 2D convnets or 3D perception algorithms.
arxiv  

Temporally Folded Convolutional Neural Networks for Sequence Forecasting [PDF]

arXiv, 2020
In this work we propose a novel approach to utilize convolutional neural networks for time series forecasting. The time direction of the sequential data with spatial dimensions $D=1,2$ is considered democratically as the input of a spatiotemporal $(D+1)$-dimensional convolutional neural network.
arxiv