In comparison to convolutional neural networks (CNN), the newly created vision transformer (ViT) has demonstrated impressive outcomes in human pose estimation (HPE). However, (1) there is a quadratic rise in complexity with respect to image size …
verfasst von:
Evans Aidoo, Xun Wang, Zhenguang Liu, Abraham Opanfo Abbam, Edwin Kwadwo Tenagyei, Victor Nonso Ejianya, Seth Larweh Kodjiku, Esther Stacy E. B. Aggrey
Knowledge distillation can transfer the knowledge from the pre-trained teacher model to the student model, thus effectively accomplishing model compression. Previous studies have carefully crafted knowledge representation, targeting loss function …
In recent years, graph neural networks (GNNs) have been widely applied in recommender systems. However, existing recommendation algorithms based on GNNs still face challenges in node aggregation and feature extraction processes because they often …
verfasst von:
Junsan Zhang, Hui Gao, Sen Xiao, Jie Zhu, Jian Wang
Graph neural networks have received increased attention over the past years due to their promising ability to handle graph-structured data, which can be found in many real-world problems such as recommender systems and drug synthesis. Most …
Facial identification for surgical and non-surgical datasets is getting popular. The reason behind this popularity is the growing need of a robust facial recognition system which is consistent to occlusion, spoofing attacks and last but most …
Named Entity Recognition (NER) plays a crucial role in the field of Natural Language Processing, holding significant value in applications such as information extraction, knowledge graphs, and question–answering systems. However, Chinese NER faces …
verfasst von:
Lei Zhang, Pengfei Xia, Xiaoxuan Ma, Chengwei Yang, Xin Ding
Dynamic multiobjective optimization is a significant challenge in accurately capturing changes in Pareto optimal sets (PS), encompassing both location and manifold changes. Existing approaches primarily focus on tracking changes in the location of …
Despite the fact that several technologies have been developed to assist healthcare workers in reducing errors and improving accuracy in illness diagnosis, there is still substantial ambiguity regarding the accurate disease diagnosis based on …
verfasst von:
B. Baranidharan, Jie Liu, G. S. Mahapatra, B. S. Mahapatra, R. Srilalithambigai
Influenced by external factors, the speed of vehicles in the traffic network is changing all the time, which makes the traditional static shortest route unable to meet the real logistics distribution needs. Considering that the existing research …
Road extraction from remote-sensing images is of great significance for vehicle navigation and emergency insurance. However, the road information extracted in the remote-sensing image is discontinuous because the road in the image is often …
In flight test engineering, the flight test duration (FTD) affects the aircraft’s delivery node and directly impacts costs. In the actual flight test process, the environmental status updates frequently, and various uncertain events are often …
The rough set (RS) and multi-granulation rough set (MGRS) theories have been successfully extended to accommodate preference analysis by substituting the equivalence relation (ER) with the dominance relation (DR). On the other hand, bipolarity …
Machine learning (ML) is an approach driven by data, and as research in machine learning progresses, the issue of noisy labels has garnered widespread attention. Noisy labels can significantly reduce the accuracy of supervised classification …
In this paper, we present HoloSLAM which is a novel solution to landmark detection issues in the simultaneous localization and mapping (SLAM) problem in autonomous robot navigation. The approach integrates real and virtual worlds to create a novel …
The class imbalance problem occurs when there is an unequal distribution of classes in a dataset and is a significant issue in various artificial intelligence applications. This study focuses on the severe multiclass imbalance problem of human …
verfasst von:
Seong Jin Bang, Min Jung Kang, Min-Goo Lee, Sang Min Lee
Group decision-making and consensus modeling have always been important research topics. With the widespread use of the Internet, group decisions can be made online, in which a large number of decision-makers participate. Most of the existing …
Artificial intelligence has made substantial progress in many medical application scenarios. The quantity and complexity of pathology images are enormous, but conventional visual screening techniques are labor-intensive, time-consuming, and …
In recent years, the field of bionics has attracted the attention of numerous scholars. Some models combined with biological vision have achieved excellent performance in computer vision and image processing tasks. In this paper, we propose a new …
The flexible job-shop scheduling problem (FJSP) with parallel batch processing machine (PBM) is one of those long-standing issues that needs cutting-edge approaches. It is a recent extension of standard flexible job shop scheduling problems.
verfasst von:
Lirui Xue, Shinan Zhao, Amin Mahmoudi, Mohammad Reza Feylizadeh
An accurate and reliable prediction of future energy patterns is of utmost significance for the smooth operation of several related activities such as capacity or generation unit planning, transmission network optimization, better resources …