Conference Information

MLUS 2027: International Conference on Machine Learning and Unmanned Systems

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Submission Date:
2027-03-13 Due in 175 days
Notification Date:
2027-04-13
Conference Date:
2027-05-28
Location:
Hangzhou, China
Years:
Viewed: 1901   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

43.4 / 100
Ranked #3,596 of 5,682 conferences · Top 64%

#247 of 469 in Robotics & Control #456 of 739 in Artificial Intelligence & Machine Learning

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
30
Community attention (10%)
17
Public record completeness (15%)
55

Inputs used: Editions on record: 2 · Researchers who opened this page in the past 24 months: 9

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-19

Call For Papers

MLUS 2027 (International Conference on Machine Learning and Unmanned Systems) is an academic conference held in Hangzhou, China on 2027-05-28. The paper submission deadline is 2027-03-13. Acceptance notifications are sent on 2027-04-13.

The topics of interest for submission include, but are not limited to: Track 1: Machine Learning Theory & Algorithms Supervised and unsupervised learning Deep learning architectures Reinforcement learning Transfer learning and domain adaptation Federated learning Graph neural networks Generative adversarial networks Explainable and interpretable AI Large-scale model training Model compression and distillation Multimodal learning Few-shot and zero-shot learning Probabilistic and Bayesian methods Online and incremental learning Benchmarking and evaluation methodologies Track 2: Perception & Sensing for Unmanned Systems Image recognition and classification Object detection and tracking Scene understanding and semantic segmentation 3D vision and reconstruction LiDAR and depth sensing Multispectral and infrared imaging Point cloud processing Visual navigation and localization Sensor fusion and integration Multimodal perception systems Real-time perception and edge processing Anomaly and fault detection Event-based and neuromorphic vision Adverse-condition perception Synthetic data and simulation for perception Track 3: Communication & Networking UAV and ad-hoc communication networks Signal processing and optimization Image and video transmission Multi-channel data fusion Cooperative communication protocols Low-power and energy-efficient communication Self-organizing and mesh networks Interference suppression and robustness Integrated space-air-ground networks Cognitive radio and dynamic spectrum access 5G/6G-enabled communication Delay-tolerant networking Network security and resilience Communication-aware path planning Quantum communication and security Track 4: Control & Autonomous Systems Intelligent and adaptive control Distributed and decentralized control Path planning and obstacle avoidance Trajectory optimization Swarm intelligence and cooperative control Robust and fault-tolerant control Model predictive control Real-time decision-making and scheduling Human-machine collaborative control Multi-agent systems and coordination Learning-based control Game-theoretic decision-making Event-triggered and hybrid control Control system security Digital twin for control and validation Track 5: System Integration & Applications Intelligent transportation and autonomous logistics Environmental monitoring and disaster response Industrial inspection and automation Smart manufacturing Healthcare robotics and medical monitoring Smart cities and infrastructure inspection Precision agriculture and forestry Marine and underwater exploration Energy systems and grid monitoring Security, surveillance, and defense Modular and reconfigurable systems Hardware-software co-design Field deployment and operational experience Open-source platforms and benchmarking Standardization and regulatory frameworks Track 6: AI Frontiers & Interdisciplinary Exploration Embodied AI and simulation-to-real transfer Large language models for unmanned systems Edge AI and on-device intelligence Brain-computer interfaces Human-robot interaction Quantum machine learning Metaverse and virtual simulation Cross-domain data fusion Novel sensors and materials Green AI and sustainable computing AI safety and robustness Ethical AI and responsible innovation Privacy and trust in unmanned systems Causal inference and reasoning Interdisciplinary methodologies and paradigms
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