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: Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery; Boris Kovalerchuk,Kawa Nazemi,Ebad Banissi Book 2022

[復(fù)制鏈接]
樓主: Filament
31#
發(fā)表于 2025-3-26 23:56:39 | 只看該作者
Visualizing and Explaining Language Modelswords and phrases, clustering or neuron activations can be used to quickly understand the underlying models. This paper showcases the techniques used in some of the most popular Deep Learning for NLP visualizations, with a special focus on interpretability and explainability.
32#
發(fā)表于 2025-3-27 03:08:43 | 只看該作者
33#
發(fā)表于 2025-3-27 06:06:49 | 只看該作者
Visual Analytics of Hierarchical and Network Timeseries Modelsnd navigation through sub-graphs; hierarchical clustering of nodes; and aggregation of links and nodes. These visual analytics allow expert users to compare the many aspects of the model to their real-world knowledge helping them gain an understanding of the model and ultimately build confidence.
34#
發(fā)表于 2025-3-27 12:34:44 | 只看該作者
Visual Discovery of Malware Patterns in?Android Appsidentify anomalous and malicious software on mobile devices. The visual findings are reached through text, tree and other techniques. An app inspection tool is also provided and its usability has been evaluated with an experimental study with ten participants.
35#
發(fā)表于 2025-3-27 14:51:48 | 只看該作者
36#
發(fā)表于 2025-3-27 21:01:06 | 只看該作者
Visual Analytics for Strategic Decision Making in Technology Managementa more sophisticated market positioning. The enhancements in machine learning and artificial intelligence allow more automatic detection of early trends to create future courses and make strategic decisions. Visual Analytics combines methods of automated data analysis through machine learning method
37#
發(fā)表于 2025-3-27 22:01:14 | 只看該作者
38#
發(fā)表于 2025-3-28 03:02:29 | 只看該作者
39#
發(fā)表于 2025-3-28 07:37:47 | 只看該作者
Non-linear Visual Knowledge Discovery with Elliptic Paired Coordinatesficiency of discovering predictive machine learning models interactively using new Elliptic Paired coordinates (EPC) visualizations. It is shown that EPC are capable to visualize multidimensional data and support visual machine learning with preservation of multidimensional information in 2-D. Relat
40#
發(fā)表于 2025-3-28 12:36:58 | 只看該作者
Convolutional Neural Networks Analysis Using Concentric-Rings Interactive Visualizationto represent the layers of a deep learning model, where each circular ring encodes the feature maps of that layer. The proposed technique allows to perform analysis of tasks over time regarding a single model or a comparison between two distinct models, thus contributing to a better understanding of
 關(guān)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(wù)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(jié) 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, 2025-10-6 12:50
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
南充市| 江陵县| 金山区| 分宜县| 唐海县| 余干县| 宿州市| 阿拉善左旗| 明溪县| 南投县| 理塘县| 天津市| 南澳县| 荔波县| 汤原县| 龙山县| 碌曲县| 朝阳县| 蓬溪县| 鄯善县| 宝兴县| 中宁县| 称多县| 临安市| 祁东县| 佛冈县| 会理县| 兴安县| 扎囊县| 江油市| 梓潼县| 肥西县| 宁德市| 开封县| 获嘉县| 慈溪市| 门源| 沙田区| 武邑县| 富锦市| 谢通门县|