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CSCS' 2023: ACM Computer Science in Cars Symposium

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截稿日期:
2023-09-24
通知日期:
2023-10-27
会议日期:
2023-12-05
会议地点:
Darmstadt, Germany
届数:
7
浏览: 13706   关注: 0   参加: 0

会伴指数 (CP-I)

43.3 / 100
全站第 3,652 名 / 共 5,693 个会议 · 前 65%
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%)
56
社区关注 (10%)
8
资料公开度 (15%)
25

用到的输入: 有据可查的届次：7 · 过去 24 个月打开过本页的研究者：2 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 2026-10-04

征稿

CSCS' 2023 (ACM Computer Science in Cars Symposium) is an academic conference held in Darmstadt, Germany on 2023-12-05. The paper submission deadline is 2023-09-24. Acceptance notifications are sent on 2023-10-27.

Aim of the Event Industry, as well as academia, have made great advances working towards an overall vision of fully autonomous driving. Despite the success stories, great challenges still lie ahead of us to make this grand vision come true. On the one hand, future systems have to be yet more capable to perceive, reason, and act in complex real-world scenarios. On the other hand, these future systems have to comply with our expectations for robustness, security, and safety. ACM, as the world’s largest computing society, addresses these challenges with the ACM Computer Science in Cars Symposium (CSCS). This symposium provides a platform for industry and academia to exchange ideas and meet these future challenges jointly. The focus of the 2023 symposium is on Artificial intelligence & Security for Autonomous Vehicles. Symposium Scope Topics: Submission of contributions are invited in (but not limited to) the following key areas: Artificial Intelligence in Autonomous Systems Sensing, perception & interaction are key challenges inside and outside the vehicle. Despite the great progress, complex real-world data still poses great challenges towards reliable recognition and analysis in a large range of operating conditions. Latest Machine Learning and in particular Deep Learning techniques have resulted in high-performance approaches that have shown impressive results. Robust algorithms for semantic, geometric and dynamic perception around the vehicle Driver and interior monitoring Interpretable and explainable Deep Neural Networks Datasets and benchmarks with real and/or synthetic data as well as novel evaluation strategies Fusion of cameras with active sensors, such as LiDAR, Radar, etc. Embedded optimization of Deep Neural Networks as well as run-time optimizations Automotive Security Information technology enables connected autonomous vehicles and many new applications but also introduces new threats. For example, an attacker could manipulate safety-critical systems such as the braking system to endanger the live and limb of passengers and other road users. An attacker could also try to generate movement or behavior profiles of the vehicle user. Thus, ensuring security and privacy is of paramount importance but poses several challenges. CSCS is a forum for discussing the latest developments in the context of security and privacy for autonomous vehicles and bringing together researchers and practitioners. Secure in-vehicle communication and lightweight cryptographic protocols System security of electronic control units, gateways etc. (e.g., hardware security, OS security) Secure external communication (e.g., V2X, Internet) and protocols (e.g., secure remote update) Automotive security standardization, secure software development, security testing Automotive Security Monitoring (e.g., IDS, IPS, SIEM, SOC) Privacy-enhancing technologies and mechanisms for automotive applications Piracy, product counterfeit, and theft protection (e.g., RKE, Immobilizer) Practical Security Evaluations / Penetration Testing Safety and Security
由 Dou Sun 最后更新于

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