Dec 15, 2023 · In decision-level fusion, each input image is classified independently using a classifier such as a neural network or support vector machine. The resulting ...

Nov 29, 2023 · In this study, we introduce the U-Swin fusion model, an effective and efficient transformer-based architecture designed for the fusion of multi-focus ...

Apr 4, 2024 · In this paper, we propose a novel deep medical image fusion method based on a deep convolutional neural network (DCNN) for directly learning image features from ...

Jul 22, 2023 · In this paper, we propose a fusion method based on MST and convolutional sparse representation (CSR) to address the inherent defects of both the MST- and SR- ...

Apr 23, 2024 · Intermediate fusion involves extracting features from different imaging modalities, concatenating them, and feeding them into a classifier, generally a support ...

21 hours ago · This paper focused on multi-temporal feature extraction of eyes feature from human face images captured in two different time slots to reduce the semantic gap ...

May 22, 2024 · Intermediate fusion involves extracting features from different imaging modalities, concatenating them, and feeding them into a classifier, generally a support ...

Aug 16, 2023 · In this new domain, a fusion method is implemented on the features of the medical images, which are types of multiscale representation. The inverse multi-scale ...

Jan 24, 2024 · Compared with support vector machines, multimodal medical image fusion diagnosis had significant advantages in accuracy and specificity. This method can ...

Aug 15, 2023 · Fusing images with different focuses using support vector machines. IEEE ... Multifocus image fusion using region segmentation and spatial frequency.