Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Domain adaptation for medical image analysis: a survey
Machine learning techniques used in computer-aided medical image analysis usually suffer
from the domain shift problem caused by different distributions between source/reference …
from the domain shift problem caused by different distributions between source/reference …
Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions
The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
A decade survey of transfer learning (2010–2020)
Transfer learning (TL) has been successfully applied to many real-world problems that
traditional machine learning (ML) cannot handle, such as image processing, speech …
traditional machine learning (ML) cannot handle, such as image processing, speech …
[HTML][HTML] Deep neural network battery charging curve prediction using 30 points collected in 10 min
Accurate degradation monitoring over battery life is indispensable for the safe and durable
operation of battery-powered applications. In this work, we extend conventional capacity …
operation of battery-powered applications. In this work, we extend conventional capacity …
Transfer learning promotes 6G wireless communications: Recent advances and future challenges
In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …
accuracy, energy efficiency, and many other key performance indicator requirements are …
Deep visual domain adaptation: A survey
Deep domain adaptation has emerged as a new learning technique to address the lack of
massive amounts of labeled data. Compared to conventional methods, which learn shared …
massive amounts of labeled data. Compared to conventional methods, which learn shared …
A survey on negative transfer
Transfer learning (TL) utilizes data or knowledge from one or more source domains to
facilitate learning in a target domain. It is particularly useful when the target domain has very …
facilitate learning in a target domain. It is particularly useful when the target domain has very …
[HTML][HTML] Two-step domain adaptation for underwater image enhancement
In recent years, underwater image enhancement methods based on deep learning have
achieved remarkable results. Since the images obtained in complex underwater scenarios …
achieved remarkable results. Since the images obtained in complex underwater scenarios …
Deep facial diagnosis: deep transfer learning from face recognition to facial diagnosis
The relationship between face and disease has been discussed from thousands years ago,
which leads to the occurrence of facial diagnosis. The objective here is to explore the …
which leads to the occurrence of facial diagnosis. The objective here is to explore the …
Hsva: Hierarchical semantic-visual adaptation for zero-shot learning
Zero-shot learning (ZSL) tackles the unseen class recognition problem, transferring
semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable …
semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable …