Results 91 to 100 of about 9,064 (165)

MAML MOT: Multiple Object Tracking Based on Meta-Learning

2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
With the advancement of video analysis technology, the multi-object tracking (MOT) problem in complex scenes involving pedestrians is gaining increasing importance. This challenge primarily involves two key tasks: pedestrian detection and re-identification.
Chen, Jiayi, Deng, Chunhua
openaire   +2 more sources

Prediction method of gas content in deep coal seams based on logging parameters: A case study of the Baijiahai region in the Junggar Basin

International Journal of Coal Science & Technology
Currently, regression prediction methods based on logging data is one of the main methods for analyzing gas content of coal seams. However, the complexity of logging parameters for deep coal seams and the scarcity of measured gas content data ...
Yijie Wen, Shu Tao, Fan Yang, Yi Cui, Qinghe Jing, Jie Guo, Shida Chen, Bin Zhang, Jincheng Ye   +8 more
doaj   +1 more source

A Task-Adaptive Parameter Transformation Scheme for Model-Agnostic-Meta-Learning-Based Few-Shot Animal Sound Classification

Applied Sciences
Deep learning models that require vast amounts of training data struggle to achieve good animal sound classification (ASC) performance. Among recent few-shot ASC methods to address the data shortage problem regarding animals that are difficult to observe,
Jaeuk Moon, Eunbeen Kim, Junha Hwang, Eenjun Hwang   +3 more
doaj   +1 more source

MAML: Towards a Faster Web in Developing Regions

Proceedings of the ACM on Web Conference 2025
8 pages, 4 ...
Ayush Pandey, Matteo Varvello, Syed Ishtiaque Ahmed, Shurui Zhou, Lakshmi Subramanian, Yasir Zaki   +5 more
openaire   +2 more sources

Risk Assessment of Heavy Rain Disasters Using an Interpretable Random Forest Algorithm Enhanced by MAML

Applied Sciences
To thoroughly investigate the distribution of heavy rain disaster risks in the Beijing–Tianjin–Hebei region, this paper analyzes the spatiotemporal evolution characteristics of heavy rain disaster-inducing factors.
Yanru Fan, Yi Wang, Wenfang Xie, Bin He
doaj   +1 more source

Fault Diagnosis of Small Sample Automobile Planetary Gearboxes Based on Continuous Wavelet Transform and Model Agnostic Meta Learning

Jixie chuandong, 2022
Aiming at the problem that the vibration signal of planetary gearboxes has strong non-stationary characteristics， few fault samples and the dependence of traditional deep learning on data， an intelligent diagnosis method for planetary gearboxes based on ...
Xinxin Lu, Jun Ma, Yingcong Zhang
doaj  

Radio Frequency Fingerprint Recognition Method Based on Adaptive Energy Path Integrated Projection and Trans-MAML Method

IEEE Access
In wireless communications, radio frequency fingerprint identification (RFFI) leverages unique hardware characteristics for device recognition. This paper proposes an innovative few-shot RFFI method based on adaptive energy path integrated projection ...
Jiawei Xin, Minjie Chen, Cong Hu
doaj   +1 more source

Dynamic Sampling-Based Meta-Learning Using Multilingual Acoustic Data for Under-Resourced Speech Recognition

IEEE Access
Under-resourced automatic speech recognition (ASR) has become an active field of research and has experienced significant progress during the past decade.
I-Ting Hsieh, Chung-Hsien Wu, Zhe-Hong Zhao   +2 more
doaj   +1 more source

'Is anyone my guardian ...?' Mamlūk Under-age Rule and the Later Qalāwūnids [PDF]

, 2007
Van Steenbergen, Jo
core   +2 more sources

Few-shot meta-learning for concrete strength prediction: a model-agnostic approach with SHAP analysis

AI in Civil Engineering
Predicting concrete compressive strength with limited data remains a critical challenge in civil engineering. This study proposes a novel framework integrating Model-Agnostic Meta-Learning (MAML) with SHAP (Shapley Additive Explanations) to improve ...
Mayaz Uddin Gazi, Md. Titumir Hasan, Ponkaj Debnath   +2 more
doaj   +1 more source