Results 121 to 130 of about 2,004,297 (387)
Blind Interleaver Recognition Using Deep Learning Techniques
IEEE AccessIn digital communication systems, channel encoders and interleavers play a crucial role in mitigating the random and burst errors introduced by noisy channels.
Nayim Ahamed, Swaminathan R., B. Naveen
doaj +1 more source
A Lexicon and Depth-wise Separable Convolution Based Handwritten Text Recognition System [PDF]
arXiv, 2022 Cursive handwritten text recognition is a challenging research problem in the domain of pattern recognition. The current state-of-the-art approaches include models based on convolutional recurrent neural networks and multi-dimensional long short-term memory recurrent neural networks techniques. These methods are highly computationally extensive as well
arxiv
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
Recognition of Internal Overvoltage in Distribution Network Based on Convolutional Neural Network
Electrica, 2022 Fei Long +5 more
doaj +1 more source
Recurrent Models of Visual Attention [PDF]
, 2014 Applying convolutional neural networks to large images is computationally expensive because the amount of computation scales linearly with the number of image pixels.
Alex Graves +4 more
core
Interleaved Group Convolutions for Deep Neural Networks [PDF]
arXiv, 2017 In this paper, we present a simple and modularized neural network architecture, named interleaved group convolutional neural networks (IGCNets). The main point lies in a novel building block, a pair of two successive interleaved group convolutions: primary group convolution and secondary group convolution. The two group convolutions are complementary: (
arxiv
Advanced Functional Materials, EarlyView.This review highlights the potential of single‐atom catalysts in three key photocatalytic reactions: the hydrogen evolution reaction (HER), nitrogen reduction reaction for ammonia synthesis, and carbon dioxide reduction reaction (CO2RR) for chemical fuels.
Saad Mehmood +5 more
wiley +1 more source
Experimental Study on Long Short-term Memory Networks for Identifying P-wave Primary Phase
CT Lilun yu yingyong yanjiuIdentifying primary phases of seismic waveforms is a routine task in seismic data processing. Owing to the low efficiency of manual identification and the influence of human subjective factors, many methods for the automatic identification of the primary
Tianzhe WANG +3 more
doaj +1 more source
Combining Recurrent and Convolutional Neural Networks for Relation Classification [PDF]
arXiv, 2016 This paper investigates two different neural architectures for the task of relation classification: convolutional neural networks and recurrent neural networks. For both models, we demonstrate the effect of different architectural choices. We present a new context representation for convolutional neural networks for relation classification (extended ...
arxiv
Coarse and fine-grained automatic cropping deep convolutional neural network [PDF]
arXiv, 2020 The existing convolutional neural network pruning algorithms can be divided into two categories: coarse-grained clipping and fine-grained clipping. This paper proposes a coarse and fine-grained automatic pruning algorithm, which can achieve more efficient and accurate compression acceleration for convolutional neural networks.
arxiv