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CSCS' 2023: ACM Computer Science in Cars Symposium

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投稿締切日:
2023-09-24
通知日:
2023-10-27
開催日:
2023-12-05
開催地:
Darmstadt, Germany
開催回数:
7
閲覧: 13705   フォロー: 0   参加: 0

会伴インデックス (CP-I)

43.3 / 100
全 5,693 件中 第 3,652 位 · 上位 65%
学術的評価 (35%) データなし — 中立の基準値 50 点として算入 —
投稿の選択性 (20%) データなし — 中立の基準値 50 点として算入 —
開催回数 (20%)
56
コミュニティの注目度 (10%)
8
公開情報の充実度 (15%)
25

使用した入力: 確認できる開催回数：7 · 過去 24 か月にこのページを開いた研究者：2 人

公開情報で不足しているもの: 過去の採択率 (+4.5) · 過去の開催回 (+3.0) · 最優秀論文の記録 (+2.3)
主催者は会議を認証申請したうえで、このページから直接追加できます。スコアは毎晩再計算されます。このスコアを上げるには

信頼度 45% — スコアのうち、中立の基準値ではなく実際に観測されたデータに基づく割合。 このスコアの算出方法 · ランキングを見る · アルゴリズム版 1.1 · 算出日 2026-10-04

論文募集

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
最終更新：Dou Sun（）

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