Results 221 to 230 of about 17,255 (243)

Prime feature extraction in pyramid network

Proceedings of ICNN'95 - International Conference on Neural Networks, 2002
A simple features extraction method for a connection weights fixed multi-layer feedforward pyramid network is proposed in this paper. Pyramid network development was biologically motivated, and an innovative pattern recognition strategy is follows which divides the mapping work into neural network and coordinate feature extraction and code matching ...
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Convolutional feature pyramid fusion via attention network

2017 IEEE International Conference on Image Processing (ICIP), 2017
We present a novel fusion scheme between multiple intermediate convolutional features within convolutional neurual network (CNN) for dense correspondence estimation. In contrast to existing CNN-based descriptors that utilize a single convolutional activation, our approach jointly uses multiple intermediate features of CNN through the attention weight ...
Sangryul Jeon, Seungryong Kim, Kwanghoon Sohn   +2 more
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Feature Pyramid Fusion Network for Hyperspectral Pansharpening

IEEE Transactions on Neural Networks and Learning Systems
Hyperspectral (HS) pansharpening aims at fusing an observed HS image with a panchromatic (PAN) image, to produce an image with the high spectral resolution of the former and the high spatial resolution of the latter. Most of the existing convolutional neural networks (CNNs)-based pansharpening methods reconstruct the desired high-resolution image from ...
Wenqian Dong, Yihan Yang, Jiahui Qu, Yunsong Li, Yufei Yang, Xiuping Jia   +5 more
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RFPNet: Reorganizing feature pyramid networks for medical image segmentation

Computers in Biology and Medicine, 2023
Medical image segmentation is a crucial step in clinical treatment planning. However, automatic and accurate medical image segmentation remains a challenging task, owing to the difficulty in data acquisition, the heterogeneity and large variation of the lesion tissue.
Zhendong Wang, Jiehua Zhu, Shujun Fu, Shuwei Mao, Yangbo Ye   +4 more
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Weighted Feature Pyramid Networks for Object Detection

2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), 2019
Feature Pyramid Networks (FPN) is a popular feature extraction. However, FPN and its variants do not investigate the influence of resolution information and semantic information in the object detection. Thus, FPN and its variants cannot detect some objects on challenging images. In this paper, based on FPN, we propose to use gaussian kernel function to
Xiaohan Li, Taotao Lai, Shuaiyu Wang, Quan Chen, Changcai Yang, Riqing Chen, Jinxun Lin, Fu Zheng   +7 more
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PFDN: Pyramid Feature Decoupling Network for Single Image Deraining

IEEE Transactions on Image Processing, 2022
Restoring images degraded by rain has attracted more academic attention since rain streaks could reduce the visibility of outdoor scenes. However, most existing deraining methods attempt to remove rain while recovering details in a unified framework, which is an ideal and contradictory target in the image deraining task.
Qiang Wang, Gan Sun, Jiahua Dong, Yulun Zhang   +3 more
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Enhanced Feature Pyramid Network for Semantic Segmentation

2020 25th International Conference on Pattern Recognition (ICPR), 2021
Multi-scale feature fusion has been an effective way for improving the performance of semantic segmentation. However, current methods generally fail to consider the semantic gaps between the shallow (low-level) and deep (high-level) features and thus the fusion methods may not be optimal. In this paper, to address the issues of the semantic gap between
Mucong Ye, Jingpeng Ouyang, Ge Chen, Jing Zhang, Xiaogang Yu   +4 more
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Gated Feature Pyramid Network for Object Detection

2018
Feature pyramid is a basic component in recognition systems for detecting objects of different scales. In order to construct the feature pyramid, most existing deep learning methods combine features of different levels based on a pyramidal feature hierarchy (e.g. SSD, Faster-RCNN). However, it lacks attention to those informative features.
Xuemei Xie, Quan Liao, Lihua Ma, Xing Jin   +3 more
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Siamese Feature Pyramid Network for Visual Tracking

2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops), 2019
Visual tracking is an important technology of robot-assisted surgery in 5G-health. Recently, discriminative correlation filter (DCF) methods utilizing in-network feature hierarchy in convolutional neural networks (CNNs) have made state-of-art results in visual tracking. However, their models are complex, which can not run in real-time.
Shuo Chang, Fan Zhang, Sai Huang, Yuanyuan Yao, Xiaotong Zhao, Zhiyong Feng   +5 more
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Convolutional Neural Networks Features: Principal Pyramidal Convolution

2015
The features extracted from convolutional neural networks (CNNs) are able to capture the discriminative part of an image and have shown superior performance in visual recognition. Furthermore, it has been verified that the CNN activations trained from large and diverse datasets can act as generic features and be transferred to other visual recognition ...
Yanming Guo, Songyang Lao, Yu Liu, Liang Bai, Shi Liu, Michael S. Lew   +5 more
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