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
Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer's disease dementia: a systematic review
S Grueso, R Viejo-Sobera - Alzheimer's research & therapy, 2021 - Springer
Background An increase in lifespan in our society is a double-edged sword that entails a
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …
RGB-D salient object detection: A survey
Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …
significant object (s) in a scene, has been widely applied to various computer vision tasks …
[HTML][HTML] Optimized hybrid ensemble learning approaches applied to very short-term load forecasting
The significance of accurate short-term load forecasting (STLF) for modern power systems'
efficient and secure operation is paramount. This task is intricate due to cyclicity, non …
efficient and secure operation is paramount. This task is intricate due to cyclicity, non …
What makes multi-modal learning better than single (provably)
The world provides us with data of multiple modalities. Intuitively, models fusing data from
different modalities outperform their uni-modal counterparts, since more information is …
different modalities outperform their uni-modal counterparts, since more information is …
Hi-net: hybrid-fusion network for multi-modal MR image synthesis
Magnetic resonance imaging (MRI) is a widely used neuroimaging technique that can
provide images of different contrasts (ie, modalities). Fusing this multi-modal data has …
provide images of different contrasts (ie, modalities). Fusing this multi-modal data has …
Salient object detection: A survey
Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …
object detection, has attracted great interest in computer vision. While many models have …
Two-stage deep learning model for Alzheimer's disease detection and prediction of the mild cognitive impairment time
Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by
thinking, behavioral and memory impairments. Early prediction of conversion from mild …
thinking, behavioral and memory impairments. Early prediction of conversion from mild …
Alzheimer's disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions
Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …
disorder among the elderly and is a leading cause of dementia. AD results in significant …
[HTML][HTML] DiCyc: GAN-based deformation invariant cross-domain information fusion for medical image synthesis
Cycle-consistent generative adversarial network (CycleGAN) has been widely used for cross-
domain medical image synthesis tasks particularly due to its ability to deal with unpaired …
domain medical image synthesis tasks particularly due to its ability to deal with unpaired …
A survey of deep learning for Alzheimer's disease
Alzheimer's and related diseases are significant health issues of this era. The
interdisciplinary use of deep learning in this field has shown great promise and gathered …
interdisciplinary use of deep learning in this field has shown great promise and gathered …