Cross-dataset validation results (Accuracy, %).

<div><p>Spatiotemporal trajectory classification is essential for intelligent perception systems but faces challenges including weak separability of dynamic features, representation collapse under limited samples, and heterogeneous conflicts in multimodal data. To address these issues, w...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Chenglong Ge (2626258) (author)
مؤلفون آخرون:	Jing Zhang (23775) (author), Jianping Du (556784) (author), Jiachen Yao (22287863) (author), Tianhe Yang (433724) (author), Xuebin Wang (1788466) (author), Linyu Wang (4624090) (author)
منشور في:	2025
الموضوعات:	Biophysics Biotechnology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified lyapunov stability criteria interpretable statistical priors intelligent perception systems integrates statistical mechanics improve trajectory understanding efficient expansion strategy dual spatiotemporal adapters large language models pro outperforms state modal adaptation framework injecting domain knowledge modal adaptation art models unified modeling training data shot scenarios representation collapse public datasets new parameters multimodal data limited samples heterogeneous trajectories heterogeneous conflicts guided cross first work experimental results effective solution dynamic features classification accuracy approach incorporates ais show
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

Cross-dataset validation results (Accuracy, %).

مواد مشابهة