找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Computational Science – ICCS 2019; 19th International C Jo?o M. F. Rodrigues,Pedro J. S. Cardoso,Peter M.A Conference proceedings 2019 Spri

[復制鏈接]
樓主: interminable
11#
發(fā)表于 2025-3-23 11:54:53 | 只看該作者
A New Shape Descriptor and Segmentation Algorithm for Automated Classifying of Multiple-morphologicaar boundary of algae bodies and noisy background, since an image segmentation is the most important preprocessing step in object classification and recognition. The previously proposed approach was able to classify twelve genera of microalgae successfully; however, when we extended it to work with n
12#
發(fā)表于 2025-3-23 14:30:28 | 只看該作者
13#
發(fā)表于 2025-3-23 20:03:28 | 只看該作者
14#
發(fā)表于 2025-3-24 00:31:19 | 只看該作者
Nonlinear Dimensionality Reduction in Texture Classification: Is Manifold Learning Better Than PCA?e image descriptors, namely Gray-Level Co-occurrence Matrix features, Haralick features, Histogram of Oriented Gradients features and Local Binary Patterns are combined to characterize and discriminate textures. For patches extracted from several texture images, a concatenation of the image descript
15#
發(fā)表于 2025-3-24 04:30:54 | 只看該作者
16#
發(fā)表于 2025-3-24 08:53:19 | 只看該作者
Path-Finding with a Full-Vectorized GPU Implementation of Evolutionary Algorithms in an Online Crowdreal-time and it can handle dynamic obstacles in maps of arbitrary size. The experiments show the proposed approach outperforms other traditional path-finding algorithms (e.g. A*). The conclusions present further improvement possibilities to the proposed approach like the application of multi-object
17#
發(fā)表于 2025-3-24 12:35:16 | 只看該作者
Path-Finding with a Full-Vectorized GPU Implementation of Evolutionary Algorithms in an Online Crowdreal-time and it can handle dynamic obstacles in maps of arbitrary size. The experiments show the proposed approach outperforms other traditional path-finding algorithms (e.g. A*). The conclusions present further improvement possibilities to the proposed approach like the application of multi-objective algorithms to represent full crowd models.
18#
發(fā)表于 2025-3-24 18:27:34 | 只看該作者
19#
發(fā)表于 2025-3-24 21:17:02 | 只看該作者
978-3-030-22749-4Springer Nature Switzerland AG 2019
20#
發(fā)表于 2025-3-25 01:08:36 | 只看該作者
 關于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-11 14:48
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
昆山市| 乌海市| 崇信县| 莆田市| 进贤县| 霍林郭勒市| 两当县| 依兰县| 石嘴山市| 辽中县| 鹤壁市| 额尔古纳市| 家居| 丰宁| 凤山县| 姜堰市| 承德市| 洛扎县| 新宁县| 万载县| 乃东县| 读书| 新昌县| 临湘市| 宜章县| 清徐县| 山丹县| 九龙县| 山阴县| 凯里市| 辽阳县| 亚东县| 高青县| 闽清县| 锦州市| 嘉定区| 大化| 盘山县| 离岛区| 柘荣县| 中山市|