Multi-object tracking (MOT) is a task to identify objects in videos, however, objects with similar appearance or occlusion may cause frequent ID switching, which is the main challenge of current MOT. In this paper, we propose a novel self-cross …
verfasst von:
Xin Feng, Xiaoning Jiao, Siping Wang, Zhixian Zhang, Yan Liu
Conversational Recommender Systems (CRS) aim to provide high-quality items to users in fewer conversation rounds using natural language. Despite various attempts that have been made, there are still some problems: Previous CRS only learned item …
Deploying static wireless sensor nodes is prone to network coverage gaps, resulting in poor network coverage. In this paper, an attempt is made to improve the network coverage by moving the locations of the nodes. A surrogate-assisted sine …
Robust matching, especially the number, precision and distribution of feature point matching, directly affects the effect of 3D reconstruction. However, the existing methods rarely consider these three aspects comprehensively to improve the …
The accurate prediction of a lithium-ion battery’s State of Health is of critical importance for efficient battery health management. Existing data-driven estimation methodologies grapple with issues such as high model complexity and a dearth of …
Object detection plays a vital role in remote sensing applications. Although object detection has achieved proud results in natural images, these methods are difficult to be directly applied to remote sensing images. Remote sensing images often …
Inferring the 3D surface shape of a known template from 2D images captured by a monocular camera is a challenging problem. Due to the severely underconstrained nature of the problem, inferring shape accurately becomes particularly challenging when …
The camouflaged object segmentation model (COSM) has recently gained substantial attention due to its remarkable ability to detect camouflaged objects. Nevertheless, deep vision models are widely acknowledged to be susceptible to adversarial …
In the field of deep learning, the attention mechanism, as a technology that mimics human perception and attention processes, has made remarkable achievements. The current methods combine a channel attention mechanism and a spatial attention …
verfasst von:
Yifan Wang, Wu Wang, Yang Li, Yaodong Jia, Yu Xu, Yu Ling, Jiaqi Ma
In this paper, we introduce a distance measure on single-valued neutrosophic sets by sine function which is a generalization of intuitionistic fuzzy sine distance measure. The axiom of metric on single-valued neutrosophic sets is verified and …
verfasst von:
M. Arockia Dasan, E. Bementa, Muhammad Aslam, V. F. Little Flower
With the development of deep learning, a higher level of perception of the environment such as the semantic level can be achieved in the simultaneous localization and mapping (SLAM) domain. However, previous works did not achieve a …
verfasst von:
Weiyi Zhang, Yushi Guo, Liting Niu, Peijun Li, Zeyu Wan, Fei Shao, Cheng Nian, Fasih Ud Din Farrukh, Debing Zhang, Chun Zhang, Qiang Li, Jianwei Zhang
Network representation learning aims to map the relationship between network nodes and context nodes to a low-dimensional representation vector space. Directed network representation learning considers mapping directional of node vector.
verfasst von:
Yan Sun, Cun Zhu, JianFu Chen, Kejia Lan, Jiuchang Pei
The aspect-based sentiment analysis (ABSA) consists of two subtasks: aspect term extraction (AE) and aspect term sentiment classification (ASC). Previous research on the AE task has not adequately leveraged syntactic information and has overlooked …
Federated learning makes it possible to train a machine learning model on decentralized data. Bayesian networks are widely used probabilistic graphical models. While some research has been published on the federated learning of Bayesian networks …
verfasst von:
Florian van Daalen, Lianne Ippel, Andre Dekker, Inigo Bermejo
Rough fuzzy clustering algorithms have received extensive attention due to the excellent ability to handle overlapping and uncertainty of data. However, existing rough fuzzy clustering algorithms generally consider single view clustering, which …
Single-frame infrared small target detection is affected by the low image resolution and small target size, and is prone to the problems of small target feature loss and positional offset during continuous downsampling; at the same time, the …
verfasst von:
Xiaoyu Xu, Weida Zhan, Yichun Jiang, Depeng Zhu, Yu Chen, Jinxin Guo, Jin Li, Yanyan Liu
UAV vehicle detection based on convolutional neural network exits a key problem of information imbalance of different feature layers. Shallow features have spatial information that is beneficial to localization, but lack semantic information. On …
Previous deep multi-agent reinforcement learning (MARL) algorithms have achieved impressive results, typically in symmetric and homogeneous scenarios. However, asymmetric heterogeneous scenarios are prevalent and usually harder to solve. In this …
verfasst von:
Xiaoyang Yu, Youfang Lin, Xiangsen Wang, Sheng Han, Kai Lv
The large-scale multi-attribute group decision-making (LSMAGDM) problem has become a hot research topic in the field of decision science. An R-numbers large-scale multi-attribute group decision-making (R-LSMAGDM) model is proposed to be …
Emergent news is characterized by few labels, and news detection methods that rely on a large number of labels are difficult to apply to learned features for emerging events and are ineffective in coping with less labeled emergent news detection.