CN110211127B - 基于双相关性网络的图像分割方法 - Google Patents
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
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CN111325751B (zh) * | 2020-03-18 | 2022-05-27 | 重庆理工大学 | 基于注意力卷积神经网络的ct图像分割系统 |
CN111612800B (zh) * | 2020-05-18 | 2022-08-16 | 智慧航海(青岛)科技有限公司 | 船舶图像检索方法、计算机可读存储介质和设备 |
CN111767810B (zh) * | 2020-06-18 | 2022-08-02 | 哈尔滨工程大学 | 一种基于D-LinkNet的遥感图像道路提取方法 |
CN112163111B (zh) * | 2020-09-28 | 2022-04-01 | 杭州电子科技大学 | 一种旋转不变的语义信息挖掘方法 |
CN113344939A (zh) * | 2021-05-07 | 2021-09-03 | 西安智诊智能科技有限公司 | 一种基于细节保持网络的图像分割方法 |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107220980A (zh) * | 2017-05-25 | 2017-09-29 | 重庆理工大学 | 一种基于全卷积网络的mri图像脑肿瘤自动分割方法 |
CN107291945A (zh) * | 2017-07-12 | 2017-10-24 | 上海交通大学 | 基于视觉注意力模型的高精度服装图像检索方法及系统 |
CN109872306A (zh) * | 2019-01-28 | 2019-06-11 | 腾讯科技(深圳)有限公司 | 医学图像分割方法、装置和存储介质 |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104599262A (zh) * | 2014-12-18 | 2015-05-06 | 浙江工业大学 | 基于多通道脉冲耦合神经网络的彩色图像分割技术 |
US10095950B2 (en) * | 2015-06-03 | 2018-10-09 | Hyperverge Inc. | Systems and methods for image processing |
US10373312B2 (en) * | 2016-11-06 | 2019-08-06 | International Business Machines Corporation | Automated skin lesion segmentation using deep side layers |
KR102419136B1 (ko) * | 2017-06-15 | 2022-07-08 | 삼성전자주식회사 | 다채널 특징맵을 이용하는 영상 처리 장치 및 방법 |
CN107784647B (zh) * | 2017-09-29 | 2021-03-09 | 华侨大学 | 基于多任务深度卷积网络的肝脏及其肿瘤分割方法及系统 |
CN110070073A (zh) * | 2019-05-07 | 2019-07-30 | 国家广播电视总局广播电视科学研究院 | 基于注意力机制的全局特征和局部特征的行人再识别方法 |
-
2019
- 2019-08-01 CN CN201910704960.9A patent/CN110211127B/zh active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107220980A (zh) * | 2017-05-25 | 2017-09-29 | 重庆理工大学 | 一种基于全卷积网络的mri图像脑肿瘤自动分割方法 |
CN107291945A (zh) * | 2017-07-12 | 2017-10-24 | 上海交通大学 | 基于视觉注意力模型的高精度服装图像检索方法及系统 |
CN109872306A (zh) * | 2019-01-28 | 2019-06-11 | 腾讯科技(深圳)有限公司 | 医学图像分割方法、装置和存储介质 |
Non-Patent Citations (6)
Title |
---|
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation;Guosheng Lin 等;《arXiv》;20161125;1-11 * |
Squeeze-and-Excitation Networks;Jie Hu 等;《arXiv》;20190516;1-13 * |
TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation;Vladimir Iglovikov、Alexey Shvets;《arXiv》;20180117;1-5 * |
基于双重金字塔网络的视频目标分割方法;姜斯浩 等;《计算机应用》;20190329;1-6 * |
基于形状先验与轮廓预定位的目标分割;马北川 等;《北京工业大学学报》;20170731;第43卷(第7期);1031-1036 * |
融合特征和先验知识的车牌字符图像检测算法;罗辉武 等;《计算机工程与应用》;20110725;1-10 * |
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