会议信息

ICDLA 2026: International Conference on Deep Learning and Automation

请登录查看会议网址
免费注册:查看官网链接、跟踪截稿日期,并接收邮件提醒。
截稿日期:
2026-07-24
通知日期:
会议日期:
2026-08-03
会议地点:
Guilin, China
届数:
1
浏览: 1514   关注: 0   参加: 0
嵌入截止倒计时徽章
ICDLA
用 API 获取这条数据
搜索与榜单列表完全无需凭证;本页的完整详情需要一把免费 API 密钥。详见开发者接入页。

会伴指数 (CP-I)

38.6 / 100
全站第 5,388 名 / 共 5,693 个会议 · 前 95%

机器人与控制 第 431 / 470 人工智能与机器学习 第 699 / 742

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
19
社区关注 (10%)
21
资料公开度 (15%)
35

用到的输入: 有据可查的届次:1 · 过去 24 个月打开过本页的研究者:16 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后,可直接在这一页补上;分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据,而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-06

征稿

ICDLA 2026 (International Conference on Deep Learning and Automation) is an academic conference held in Guilin, China on 2026-08-03. The paper submission deadline is 2026-07-24.

About ICDLA 2026 The 2026 Digital Intelligence Frontier Academic Week–Guilin will take place from August 3 to 8, 2026, in Guilin, China. This premier event brings together multiple international cutting-edge conferences, focusing on deep learning, automation technologies, artificial intelligence, large language models, and intelligent systems. It aims to establish a distinguished, interdisciplinary exchange platform for scholars worldwide to jointly explore the scientific frontiers and industrial future of the digital intelligence era. As one of the major conferences of the Academic Week, the 2026 International Conference on Deep Learning and Automation (ICDLA 2026) will take place on August 4, 2026. At a time when the core driving force of AI is deeply integrated with industrial transformation, deep learning is leading automation technology into a new phase where perception, decision-making, and control are integrated. From highly adaptive intelligent manufacturing systems, to clusters of intelligent robots capable of understanding complex environments, to large-scale collaborative optimization in smart cities and smart grids, the integration of deep learning and automation is reshaping traditional industrial landscapes and expanding new frontiers in scientific research and engineering applications. ICDLA 2026 aims to gather global intelligence for in-depth discussions around core topics including deep learning models and algorithms, and intelligent automation systems. The conference will provide an international, high-end platform for scholars, engineers, and industry leaders worldwide: Here, you can share your latest research findings and demonstrate academic influence; engage in face-to-face exchanges with top experts in the field to spark innovative ideas; expand international collaboration networks and promote substantive scientific partnerships; and accurately grasp disciplinary development trends to gain insights into future research directions. The topics of interest for submission include, but are not limited to: ◕ Track1: Deep Learning Models and Algorithms Recurrent Neural Networks Sparse Coding Neuro-Fuzzy Algorithms Evolutionary Computation Methods Convolutional Neural Networks Deep Hierarchical Networks Unsupervised Feature Learning Deep Boltzmann Machines Generative Adversarial Networks, Autoencoder Deep Belief Networks Meta-Learning and Deep Networks Deep Reinforcement Learning Deep Generative Model Learning Deep Kernel Learning Gaussian Processes in Machine Learning Large-Scale Model Deployment Lightweight Models Generative Automation Federated Intelligence ◕Track2: Intelligent Automation Systems Scientific Research Agents Industrial Intelligent Manufacturing Intelligent Robotics Automated Inspection Cyber-Physical Systems Unmanned Systems Process Automation Intelligent Sensing and Fusion Automated Scheduling Edge Intelligence Human-Machine Collaborative Systems Medical Automation Energy Automation Multimodal Automated Perception Intelligent Decision-Making Cross-Domain Automation Real-Time Intelligent Scheduling Trustworthy Automation Verification Edge Collaborative Automation Dynamic Scenario Automation Human-Machine Collaborative Decision-Making Publication All accepted full papers will be published in the conference proceedings and will be submitted to EI Compendex / Scopus for indexing.
由 Dou Sun 最后更新于

相关期刊

CCF全称影响因子出版商ISSN
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536
AIEEE Transactions on Dependable and Secure Computing7.5IEEE1545-5971

评论 0

暂无评论。

请登录后发表评论