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ICRMV 2027: International Conference on Robotics and Machine Vision

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ICRMV
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투고 마감일:
2026-11-01 46일 남음
통보일:
2026-12-01
개최일:
2027-03-19
개최지:
Haining, China
개최 횟수:
조회: 15634   팔로우: 0   참가: 0

회반 지수 (CP-I)

50.5 / 100
전체 5,682개 중 1,471위 · 상위 26%

로보틱스·제어 분야 469개 중 63위 컴퓨터 비전·패턴 인식 분야 244개 중 63위

학술적 인정 (35%) 데이터 없음 — 중립 기준값 50점으로 계산
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산
개최 횟수 (20%)
67
커뮤니티 관심도 (10%)
13
공개 자료 충실도 (15%)
55

사용한 입력: 확인되는 개최 횟수: 11 · 지난 24개월 동안 이 페이지를 연 연구자: 5명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 최우수 논문 기록 (+2.3)
주최자는 학회를 인증 신청한 뒤 이 페이지에서 바로 추가할 수 있습니다. 점수는 매일 밤 다시 계산됩니다. 이 점수를 올리는 방법

신뢰도 45% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.1 · 산출일 2026-09-15

논문 모집

ICRMV 2027 (International Conference on Robotics and Machine Vision) is an academic conference held in Haining, China on 2027-03-19. The paper submission deadline is 2026-11-01. Acceptance notifications are sent on 2026-12-01.

The conference focuses on innovative and original research results in robotics, machine vision, and their integration through learning-based approaches. Both theoretical papers and experimental/simulation studies are welcome. Topics of interest include, but are not limited to: 1. Machine Learning in Robotics Supervised, unsupervised, and reinforcement learning for robotics Adaptive and autonomous robot control systems Robot learning from demonstration and imitation Learning-based motion planning and navigation Multi-robot learning and coordination Transfer learning and domain adaptation for robotic applications 2. Deep Learning in Robotics Deep reinforcement learning for robotic control Convolutional Neural Networks (CNNs) for robotic perception Recurrent Neural Networks (RNNs) for sequential robot tasks Deep learning for robot localization and mapping (SLAM) End-to-end learning for robotic manipulation and locomotion Self-supervised and semi-supervised learning for robotics 3. Machine Vision and Perception Image and video analysis for robotic applications 3D vision, structure from motion, and depth perception Visual tracking, object detection, and pose estimation Semantic and instance segmentation for scene understanding Vision-based manipulation, grasping, and tactile-visual integration Sensor fusion (vision, LiDAR, radar, IMU) and multi-modal perception 4. Robotics Fundamentals and Control Robot kinematics, dynamics, and motion planning Multi-robot systems, swarm robotics, and coordination Human-robot interaction and collaborative robotics Soft robotics, bio-inspired robotics, and reconfigurable robots Robot perception, state estimation, and sensor networks Real-time and embedded control architectures 5. Applications of Machine Learning and Vision in Robotics Healthcare, surgical, and rehabilitation robotics Industrial automation, manufacturing, and logistics Autonomous vehicles, drones, and intelligent transportation systems Service, social, and assistive robotics Agricultural, field, and forestry robotics Exploration, search and rescue, and planetary robotics 6. Theoretical Foundations and Real-World Deployments Advances in neural network architectures for robotic vision Statistical learning, scalability, and real-time efficiency Explainability, interpretability, and safety of robotic learning models Robustness, generalization, and domain adaptation in real-world environments Benchmarking, performance evaluation, and case studies of deployed systems Ethical considerations, legal frameworks, and human-centric design
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AA*89.3STOCACM Symposium on Theory of Computing2025-11-042026-06-22
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관련 저널

CCF정식 명칭영향력 지수출판사ISSN
CMachine Vision and Applications2.3Springer0932-8092
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

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