|
|
|
|
|
Chuanyun Xu, Hang Wang, Yang Zhang, Zheng Zhou and Gang Li
Few-shot learning refers to training a model with a few labeled data to effectively recognize unseen categories. Recently, numerous approaches have been suggested to improve the extraction of abundant feature information at hierarchical layers or multipl...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yiming Mo, Lei Wang, Wenqing Hong, Congzhen Chu, Peigen Li and Haiting Xia
The intrusion of foreign objects on airport runways during aircraft takeoff and landing poses a significant safety threat to air transportation. Small-scale Foreign Object Debris (FOD) cannot be ruled out on time by traditional manual inspection, and the...
ver más
|
|
|
|
|
|
|
|
|
|
|
|
Shuang Che, Yan Chen, Longda Wang and Chuanfang Xu
This work discusses the electric vehicle (EV) ordered charging planning (OCP) optimization problem. To address this issue, an improved dual-population genetic moth?flame optimization (IDPGMFO) is proposed. Specifically, to obtain an appreciative solution...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mirko Dinulovic, Aleksandar Benign and Bo?ko Ra?uo
In the present work, the potential application of machine learning techniques in the flutter prediction of composite materials missile fins is investigated. The flutter velocity data set required for different fin aerodynamic geometries and materials is ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Baoyu Fan, Han Ma, Yue Liu and Xiaochen Yuan
With the growth of data in the real world, datasets often encounter the problem of long-tailed distribution of class sample sizes. In long-tailed image recognition, existing solutions usually adopt a class rebalancing strategy, such as reweighting based ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ziyi Wang, Xinran Li, Luoyang Sun, Haifeng Zhang, Hualin Liu and Jun Wang
Efficient yet sufficient exploration remains a critical challenge in reinforcement learning (RL), especially for Markov Decision Processes (MDPs) with vast action spaces. Previous approaches have commonly involved projecting the original action space int...
ver más
|
|
|
|
|
|
|
|
|
|
|
Longde Wang, Hui Cao, Zhichao Cui and Zeren Ai
Marine engines confront challenges of varying working conditions and intricate failures. Existing studies have primarily concentrated on fault diagnosis in a single condition, overlooking the adaptability of these methods in diverse working condition. To...
ver más
|
|
|
|
|
|
|
|
|
|
|
Pengfei Zhao and Ze Liu
The three-dimensional (3D) reconstruction of Electromagnetic Tomography (EMT) is an important task for many applications, such as the non-destructive testing of inner defects in rail systems. Additionally, image reconstruction algorithms utilizing deep l...
ver más
|
|
|
|
|
|