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Arguments for the Unsuitability of Convolutional Neural Networks for Non–Local Tasks [article]

Sebastian Stabinger, David Peer, Antonio Rodríguez-Sánchez
2021 arXiv   pre-print
Convolutional neural networks have established themselves over the past years as the state of the art method for image classification, and for many datasets, they even surpass humans in categorizing images  ...  We will use this insight to reformulate a comparison task into a sorting task and use findings on sorting networks to propose a lower bound for the number of parameters a neural network needs to solve  ...  Hypothesis: Problems exhibiting low locality are ill fitted to be solved by Convolutional Neural Networks (CNNs) Intuitively, CNNs are ill suited to solve non-local tasks, since the convolutional part  ... 
arXiv:2102.11944v1 fatcat:6wgyd5ctzjhcfaidpo4zifosb4

Arguments for the unsuitability of convolutional neural networks for non–local tasks

Sebastian Stabinger, David Peer, Antonio Rodríguez-Sánchez
2021 Neural Networks  
Convolutional neural networks have established themselves over the past years as the state of the art method for image classification, and for many datasets, they even surpass humans in categorizing images  ...  We will use this insight to reformulate a comparison task into a sorting task and use findings on sorting networks to propose a lower bound for the number of parameters a neural network needs to solve  ...  Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper  ... 
doi:10.1016/j.neunet.2021.05.001 pmid:34000564 fatcat:aqnwm6ci3ner7ixnrx2tk5xfza

Extensive Facial Landmark Localization with Coarse-to-Fine Convolutional Network Cascade

Erjin Zhou, Haoqiang Fan, Zhimin Cao, Yuning Jiang, Qi Yin
2013 2013 IEEE International Conference on Computer Vision Workshops  
Deep convolutional neural networks (DCNN) have been successfully utilized in facial landmark localization for two-fold advantages: 1) geometric constraints among facial points are implicitly utilized;  ...  the structure design and training process of traditional convolutional networks.  ...  To validate the effectiveness of our structure, we show that our system can achieve good performance in the 300-W facial landmark localization challenge.  ... 
doi:10.1109/iccvw.2013.58 dblp:conf/iccvw/ZhouFCJY13 fatcat:hbcqsxeqyrd6fg2pcomccydyo4

Accelerating Event Detection with DGCNN and FPGAs

Zhe Han, Jingfei Jiang, Linbo Qiao, Yong Dou, Jinwei Xu, Zhigang Kan
2020 Electronics  
In order to solve this problem, we proposed a network model based on the dilate gated convolutional neural network, which is very hardware-friendly.  ...  We further expanded the word representations and depth of the network to improve the performance of the model.  ...  In particular, convolutional layers are the heart of the convolutional neural network, which often occupy the main part of the computation of the entire convolutional neural network.  ... 
doi:10.3390/electronics9101666 fatcat:uoabndnjgfgf7ajwyozs33f47q

Graph Neural Networks: A Review of Methods and Applications [article]

Jie Zhou, Ganqu Cui, Shengding Hu, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, Maosong Sun
2021 arXiv   pre-print
Graph neural networks (GNNs) are neural models that capture the dependence of graphs via message passing between the nodes of graphs.  ...  In recent years, variants of GNNs such as graph convolutional network (GCN), graph attention network (GAT), graph recurrent network (GRN) have demonstrated ground-breaking performances on many deep learning  ...  The non-local neural network (NLNN) generalizes and extends the classic non-local mean operation (Buades et al., 2005) in computer vision.  ... 
arXiv:1812.08434v6 fatcat:ncz44kny6nairjjnysrqd5qjoi

A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference [article]

Kumar Shridhar, Felix Laumann, Marcus Liwicki
2019 arXiv   pre-print
We, therefore, introduce the idea of applying two convolutional operations, one for the mean and one for the variance.  ...  Artificial Neural Networks are connectionist systems that perform a given task by learning on examples without having prior knowledge about the task.  ...  42, 28] , for training recurrent neural networks [11] , but has not been applied to convolutional neural networks to-date.  ... 
arXiv:1901.02731v1 fatcat:2lxt22pjifbobnlmkbolcaybby

Methods for image denoising using convolutional neural network: a review

Ademola E. Ilesanmi, Taiwo O. Ilesanmi
2021 Complex & Intelligent Systems  
Convolutional neural network (CNN) has increasingly received attention in image denoising task. Several CNN methods for denoising images have been studied.  ...  AbstractImage denoising faces significant challenges, arising from the sources of noise. Specifically, Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in imaging.  ...  Special thanks to the management of Alex Ekwueme Federal University, Ndufu-Alike for support during this research. The authors express thanks to Professor Stanislav S.  ... 
doi:10.1007/s40747-021-00428-4 fatcat:3e3efpzdc5bm5cte2nvdvurnki

Discovering Molecular Functional Groups Using Graph Convolutional Neural Networks [article]

Phillip Pope, Soheil Kolouri, Mohammad Rostrami, Charles Martin, Heiko Hoffmann
2019 arXiv   pre-print
In this paper, we investigate methods based on graph convolutional neural networks (GCNNs) for localizing FGs that contribute to specific chemical properties of interest.  ...  Although these methods are originally derived for convolutional neural networks (CNNs), we adapt them to develop the corresponding suitable versions for GCNNs.  ...  Using the specific class of Deep convolutional neural networks (CNNs) on vision tasks has led to human-level performance on classification [20] and object detection [39] tasks.  ... 
arXiv:1812.00265v3 fatcat:v3zav2o3ljhrvf7dzvoj4hyrj4

Semi-convolutional Operators for Instance Segmentation [article]

David Novotny, Samuel Albanie, Diane Larlus, Andrea Vedaldi
2018 arXiv   pre-print
We use the latter to show a connection to Hough voting as well as to a variant of the bilateral kernel that is spatially steered by a convolutional network.  ...  At the same time, we show that simple modifications, which we call semi-convolutional, have a much better chance of succeeding at this task.  ...  We gratefully acknowledge the support of Naver, EPSRC AIMS CDT, AWS ML Research Award, and ERC 677195-IDIU.  ... 
arXiv:1807.10712v1 fatcat:4rrkteninvbklayyoo6h5pr5ti

Semi-convolutional Operators for Instance Segmentation [chapter]

David Novotny, Samuel Albanie, Diane Larlus, Andrea Vedaldi
2018 Lecture Notes in Computer Science  
We use the latter to show a connection to Hough voting as well as to a variant of the bilateral kernel that is spatially steered by a convolutional network.  ...  At the same time, we show that simple modifications, which we call semi-convolutional, have a much better chance of succeeding at this task.  ...  We gratefully acknowledge the support of Naver, EPSRC AIMS CDT, AWS ML Research Award, and ERC 677195-IDIU.  ... 
doi:10.1007/978-3-030-01246-5_6 fatcat:2aj4m23z7fglhbmvyovqzjf2bi

Flex-Convolution (Million-Scale Point-Cloud Learning Beyond Grid-Worlds) [article]

Fabian Groh, Patrick Wieschollek, Hendrik P.A. Lensch
2020 arXiv   pre-print
In this work, we introduce a natural generalization flex-convolution of the conventional convolution layer along with an efficient GPU implementation.  ...  Traditional convolution layers are specifically designed to exploit the natural data representation of images -- a fixed and regular grid.  ...  For these tasks, research has led to several improved neural network architectures ranging from VGG [24] to ResNet [9] .  ... 
arXiv:1803.07289v4 fatcat:3czwn4i4svbhhfma53zdtcjwva

Prompt Agnostic Essay Scorer: A Domain Generalization Approach to Cross-prompt Automated Essay Scoring [article]

Robert Ridley, Liang He, Xinyu Dai, Shujian Huang, Jiajun Chen
2020 arXiv   pre-print
Since obtaining a large quantity of pre-graded essays to a particular prompt is often difficult and unrealistic, the task of cross-prompt AES is vital for the development of real-world AES systems, yet  ...  Cross-prompt automated essay scoring (AES) requires the system to use non target-prompt essays to award scores to a target-prompt essay.  ...  Model Following the effectiveness of representing the hierarchical structure of essays in the task of prompt-specific AES, we adopt an attention-based recurrent convolutional neural network [8] as our  ... 
arXiv:2008.01441v1 fatcat:4faj6ifdendo5et2dzxfybpme4

The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification [article]

Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loic Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair, Sujal Desai, Ben Glocker, Julia A. Schnabel
2021 arXiv   pre-print
In lung nodule classification, for example, many works report results on the publicly available LIDC dataset.  ...  In theory, this should allow a direct comparison of the performance of proposed methods and assess the impact of individual contributions.  ...  as a convolutional neural network (CNN).  ... 
arXiv:2108.05386v1 fatcat:l7ahpm25jzg4zjoub2rhppwrxu

Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions [article]

Fouzia Altaf, Syed M. S. Islam, Naveed Akhtar, Naeem K. Janjua
2019 arXiv   pre-print
This article does not assume prior knowledge of Deep Learning and makes a significant contribution in explaining the core Deep Learning concepts to the non-experts in the Medical community.  ...  provide promising directions for the Medical Imaging community to fully harness Deep Learning in the future.  ...  Convolutional Neural Networks In the context of DL techniques for image analysis, Convolution Neural Networks (CNNs) [23] , [29] are of the primary importance.  ... 
arXiv:1902.05655v1 fatcat:mjplenjrprgavmy5ssniji4cam

Graph Neural Networks as a Potential Tool in Improving Virtual Screening Programs

Luiz Anastacio Alves, Natiele Carla da Silva Ferreira, Victor Maricato, Anael Viana Pinto Alberto, Evellyn Araujo Dias, Nt Jose Aguiar Coelho
2022 Frontiers in Chemistry  
In this context, graph neural networks (GNN), a recent deep-learning subtype, may comprise a powerful tool to improve VS results concerning natural products that may be used both simultaneously with standard  ...  Despite the increasing number of pharmaceutical companies, university laboratories and funding, less than one percent of initially researched drugs enter the commercial market.  ...  We also thank the Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) for the financial support ("Redes de Pesquisa em Saúde no Estado do Rio de Janeiro" -Grant number  ... 
doi:10.3389/fchem.2021.787194 pmid:35127645 pmcid:PMC8811035 fatcat:o2gkjdhxf5d23ipfygmdoz2p3e
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