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We propose a new CNN-CRF end-to-end learning framework, which is based on joint stochastic optimization with respect to both Convolutional Neural Network (CNN) and Conditional Random Field (CRF) parameters. While stochastic gradient descent…

Computer Vision and Pattern Recognition · Computer Science 2016-09-15 Alexander Kirillov , Dmitrij Schlesinger , Shuai Zheng , Bogdan Savchynskyy , Philip H. S. Torr , Carsten Rother

Despite their black-box nature, deep learning models are extensively used in image-based drug discovery to extract feature vectors from single cells in microscopy images. To better understand how these networks perform representation…

Image and Video Processing · Electrical Eng. & Systems 2024-03-27 Vivek Gopalakrishnan , Jingzhe Ma , Zhiyong Xie

Learning distributed representations for nodes in graphs is a crucial primitive in network analysis with a wide spectrum of applications. Linear graph embedding methods learn such representations by optimizing the likelihood of both…

Machine Learning · Computer Science 2018-10-16 Yihan Gao , Chao Zhang , Jian Peng , Aditya Parameswaran

Network embedding techniques aim at representing structural properties of graphs in geometric space. Those representations are considered useful in downstream tasks such as link prediction and clustering. However, the number of graph…

Physics and Society · Physics 2021-11-03 Yi-Jiao Zhang , Kai-Cheng Yang , Filippo Radicchi

Recently a variety of methods have been developed to encode graphs into low-dimensional vectors that can be easily exploited by machine learning algorithms. The majority of these methods start by embedding the graph nodes into a…

Machine Learning · Computer Science 2018-09-13 Yu Jin , Joseph F. JaJa

Understanding how cities visually differ from each others is interesting for planners, residents, and historians. We investigate the interpretation of deep features learned by convolutional neural networks (CNNs) for city recognition. Given…

Computer Vision and Pattern Recognition · Computer Science 2019-05-07 Xiangwei Shi , Seyran Khademi , Jan van Gemert

Multi-label image and video classification are fundamental yet challenging tasks in computer vision. The main challenges lie in capturing spatial or temporal dependencies between labels and discovering the locations of discriminative…

Computer Vision and Pattern Recognition · Computer Science 2020-03-30 Renchun You , Zhiyao Guo , Lei Cui , Xiang Long , Yingze Bao , Shilei Wen

A meningioma is a type of brain tumor that requires tumor volume size follow ups in order to reach appropriate clinical decisions. A fully automated tool for meningioma detection is necessary for reliable and consistent tumor surveillance.…

Computer Vision and Pattern Recognition · Computer Science 2018-05-30 Sungmin Lee , Jangho Lee , Jungbeom Lee , Chul-Kee Park , Sungroh Yoon

Social network analysis provides meaningful information about behavior of network members that can be used for diverse applications such as classification, link prediction. However, network analysis is computationally expensive because of…

Social and Information Networks · Computer Science 2018-07-30 Mohammad Mehdi Keikha , Maseud Rahgozar , Masoud Asadpour

Neural network quantization is a critical technique for deploying models on resource-limited devices. Despite its widespread use, the impact of quantization on model perceptual fields, particularly in relation to class activation maps…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Mohamed Amine Kerkouri , Marouane Tliba , Aladine Chetouani , Alessandro Bruno

In this paper, we propose a new deep learning network "GENet", it combines the multi-layer network architec- ture and graph embedding framework. Firstly, we use simplest unsupervised learning PCA/LDA as first layer to generate the low-…

Computer Vision and Pattern Recognition · Computer Science 2014-09-26 Yufei Gan , Teng Yang , Chu He

Graph convolutional neural network (GCN) has drawn increasing attention and attained good performance in various computer vision tasks, however, there lacks a clear interpretation of GCN's inner mechanism. For standard convolutional neural…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Zhenpeng Feng , Xiyang Cui , Hongbing Ji , Mingzhe Zhu , Ljubisa Stankovic

Classifying large scale networks into several categories and distinguishing them according to their fine structures is of great importance with several applications in real life. However, most studies of complex networks focus on properties…

Computer Vision and Pattern Recognition · Computer Science 2022-09-07 Ruyue Xin , Jiang Zhang , Yitong Shao

Instead of using current deep-learning segmentation models (like the UNet and variants), we approach the segmentation problem using trained Convolutional Neural Network (CNN) classifiers, which automatically extract important features from…

Image and Video Processing · Electrical Eng. & Systems 2022-01-31 Shuyue Guan , Murray Loew

We propose a new regularization method to alleviate over-fitting in deep neural networks. The key idea is utilizing randomly transformed training samples to regularize a set of sub-networks, which are originated by sampling the width of the…

Computer Vision and Pattern Recognition · Computer Science 2020-10-14 Taojiannan Yang , Sijie Zhu , Chen Chen

Network embedding, which aims to learn low-dimensional representations of nodes, has been used for various graph related tasks including visualization, link prediction and node classification. Most existing embedding methods rely solely on…

Social and Information Networks · Computer Science 2019-08-22 Palash Goyal , Homa Hosseinmardi , Emilio Ferrara , Aram Galstyan

In this paper we propose an implement a general convolutional neural network (CNN) building framework for designing real-time CNNs. We validate our models by creating a real-time vision system which accomplishes the tasks of face detection,…

Computer Vision and Pattern Recognition · Computer Science 2017-10-23 Octavio Arriaga , Matias Valdenegro-Toro , Paul Plöger

Image classification is a fundamental task in computer vision with diverse applications, ranging from autonomous systems to medical imaging. The CIFAR-10 dataset is a widely used benchmark to evaluate the performance of classification…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Xiaoran Yang , Shuhan Yu , Wenxi Xu

Existing network embedding approaches tackle the problem of learning low-dimensional node representations. However, networks can also be seen in the light of edges interlinking pairs of nodes. The broad goal of this paper is to introduce…

Social and Information Networks · Computer Science 2020-11-12 Giuseppe Pirrò

Image classification has been studied extensively, but there has been limited work in using unconventional, external guidance other than traditional image-label pairs for training. We present a set of methods for leveraging information…

Computer Vision and Pattern Recognition · Computer Science 2020-04-28 Ankit Dhall , Anastasia Makarova , Octavian Ganea , Dario Pavllo , Michael Greeff , Andreas Krause
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