A survey of recommendation systems: recommendation models, techniques, and application fields
This paper reviews the research trends that link the advanced technical aspects of
recommendation systems that are used in various service areas and the business aspects of …
recommendation systems that are used in various service areas and the business aspects of …
Automatic defect detection of metro tunnel surfaces using a vision-based inspection system
Due to the impact of the surrounding environment changes, train-induced vibration, and
human interference, damage to metro tunnel surfaces frequently occurs. Therefore …
human interference, damage to metro tunnel surfaces frequently occurs. Therefore …
Hybrid contrastive learning for unsupervised person re-identification
Unsupervised person re-identification (Re-ID) aims to learn discriminative features without
human-annotated labels. Recently, contrastive learning has provided a new prospect for …
human-annotated labels. Recently, contrastive learning has provided a new prospect for …
Diabetic retinopathy detection and stage classification in eye fundus images using active deep learning
Retinal fundus image analysis (RFIA) for diabetic retinopathy (DR) screening can be used to
reduce the risk of blindness among diabetic patients. The RFIA screening programs help the …
reduce the risk of blindness among diabetic patients. The RFIA screening programs help the …
A full migration BBO algorithm with enhanced population quality bounds for multimodal biomedical image registration
Medical images acquired from different modalities give rise to many practical problems in
image registration. Intensity-based registration techniques have been increasingly used in …
image registration. Intensity-based registration techniques have been increasingly used in …
A reliable deep representation learning to improve trust-aware recommendation systems
Deep neural networks have been extensively employed in many applications such as
natural language processing and computer vision. They have attracted a lot of attention in …
natural language processing and computer vision. They have attracted a lot of attention in …
MLFS-CCDE: multi-objective large-scale feature selection by cooperative coevolutionary differential evolution
Feature selection is a pre-processing procedure of choosing the optimal feature subsets for
constructing model, yet it is difficult to satisfy the requirements of reducing number of …
constructing model, yet it is difficult to satisfy the requirements of reducing number of …
Deep learning-based collaborative filtering recommender systems: A comprehensive and systematic review
Nowadays, the volume of online information is growing and it is difficult to find the required
information. Effective strategies such as recommender systems are required to overcome …
information. Effective strategies such as recommender systems are required to overcome …
A kernel correlation-based approach to adaptively acquire local features for learning 3D point clouds
Abstract 3D models are used in a variety of CAX fields, and their key is 3D data geometry
and semantic perception. However, semantic learning of 3D point clouds is a challenge due …
and semantic perception. However, semantic learning of 3D point clouds is a challenge due …
3D mesh simplification with feature preservation based on whale optimization algorithm and differential evolution
Large-scale 3D models consume large computing and storage resources. To address this
challenging problem, this paper proposes a new method to obtain the optimal simplified 3D …
challenging problem, this paper proposes a new method to obtain the optimal simplified 3D …