Results 281 to 290 of about 949,168 (327)

Robust Attentional Pooling via Feature Selection

2018 24th International Conference on Pattern Recognition (ICPR), 2018
In this paper we propose a novel network module, namely Robust Attentional Pooling (RAP), that potentially can be applied in an arbitrary network for generating single vector representations for classification. By taking a feature matrix for each data sample as the input, our RAP learns data-dependent weights that are used to generate a vector through ...
Jian Zheng, Teng-Yok Lee, Chen Feng, Xiaohua Lit, Ziming Zhang   +4 more
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Feature Pooling by Learning

2015
In learning-based image quality assessment, images are represented by features with low dimension much less than the size of image. The features can be obtained by the aid of priori knowledge that people have gained; for example, the aforementioned basic and advantage features.
Long Xu, Weisi Lin, C.-C. Jay Kuo
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Features-Pooling Blind JPEG Image Steganalysis

2008 Digital Image Computing: Techniques and Applications, 2008
In this research, we introduce a new blind steganalysis in detecting grayscale JPEG images. Features-pooling method is employed to extract the steganalytic features and the classification is done by using neural network. Three different steganographic models are tested and classification results are compared to the five state-of-the-art blind ...
Leng, Chiew, Pieprzyk, Josef
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Feature pooling for small visual dictionaries

SPIE Proceedings, 2016
Large visual dictionaries are often used to achieve good image classification performance in bag-of-features (BoF) model, while they lead to high computational cost on dictionary learning and feature coding. In contrast, using small dictionaries can largely reduce the computational cost but result in poor classification performance.
Xianglin Huang, Ye Xu, Lifang Yang, Jianglong Zhang   +3 more
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Global Feature Guided Local Pooling

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019
In deep convolutional neural networks (CNNs), local pooling operation is a key building block to effectively downsize feature maps for reducing computation cost as well as increasing robustness against input variation. There are several types of pooling operation, such as average/max-pooling, from which one has to be manually selected for building CNNs.
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Spatial Pooling of Heterogeneous Features for Image Classification

IEEE Transactions on Image Processing, 2014
In image classification tasks, one of the most successful algorithms is the bag-of-features (BoFs) model. Although the BoF model has many advantages, such as simplicity, generality, and scalability, it still suffers from several drawbacks, including the limited semantic description of local descriptors, lack of robust structures upon single visual ...
Lingxi, Xie, Qi, Tian, Meng, Wang, Bo, Zhang   +3 more
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Street View Image Retrieval with Average Pooling Features

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
Street view image retrieval is a challenging subject due to the complexity of the street view. Such images contain a large number of similarly structured buildings and are obscured by other objects such as pedestrians and vehicles. In this paper, we present a street view image retrieval system based on average pooling features and SIFT (Scale-invariant
Tianyou Chu, Yumin Chen, Liheng Huang, Huangyuan Tan, Jiping Cao, Zhiqiang Xu   +5 more
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Deep regional feature pooling for video matching

2017 IEEE International Conference on Image Processing (ICIP), 2017
In this work, we study the problem of deep global descriptors for video matching with regional feature pooling. We aim to analyze the joint effect of ROI (Region of Interest) size and pooling moment on video matching performance. To this end, we propose to mathematically model the distribution of video matching function with a pooling function nested ...
Yan Bai, Jie Lin, Vijay Chandrasekhar, Yihang Lou, Shiqi Wang, Ling-Yu Duan, Tiejun Huang, Alex Kot   +7 more
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Human action recognition from simple feature pooling

Pattern Analysis and Applications, 2012
Human action recognition (HAR) from images is an important and challenging task for many current applications. In this context, designing discriminative action descriptors from simple features is a relevant task. In this paper we show that very good descriptors can be build from simple filter outputs when multilevel architectures and non-linear ...
Manuel J. Marín-Jiménez, Nicolás Pérez de la Blanca, M. Ángeles Mendoza   +2 more
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Task-Driven Feature Pooling for Image Classification

2015 IEEE International Conference on Computer Vision (ICCV), 2015
Feature pooling is an important strategy to achieve high performance in image classification. However, most pooling methods are unsupervised and heuristic. In this paper, we propose a novel task-driven pooling (TDP) model to directly learn the pooled representation from data in a discriminative manner.
Guo-Sen Xie, Xu-Yao Zhang, Xiangbo Shu, Shuicheng Yan, Cheng-Lin Liu   +4 more
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