AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 9041 to 9050 of 10288 articles

Enabling scale and rotation invariance in convolutional neural networks with retina like transformation.

Neural networks : the official journal of the International Neural Network Society
Traditional convolutional neural networks (CNNs) struggle with scale and rotation transformations, resulting in reduced performance on transformed images. Previous research focused on designing specific CNN modules to extract transformation-invariant...

LUNETR: Language-Infused UNETR for precise pancreatic tumor segmentation in 3D medical image.

Neural networks : the official journal of the International Neural Network Society
The identification of early micro-lesions and adjacent blood vessels in CT scans plays a pivotal role in the clinical diagnosis of pancreatic cancer, considering its aggressive nature and high fatality rate. Despite the widespread application of deep...

Unambiguous granularity distillation for asymmetric image retrieval.

Neural networks : the official journal of the International Neural Network Society
Previous asymmetric image retrieval methods based on knowledge distillation have primarily focused on aligning the global features of two networks to transfer global semantic information from the gallery network to the query network. However, these m...

Spatial and frequency information fusion transformer for image super-resolution.

Neural networks : the official journal of the International Neural Network Society
Previous works have indicated that Transformer-based models bring impressive image reconstruction performance in single image super-resolution (SISR). However, existing Transformer-based approaches utilize self-attention within non-overlapping window...

Multi-level semantic-aware transformer for image captioning.

Neural networks : the official journal of the International Neural Network Society
Effective visual representation is crucial for image captioning task. Among the existing methods, the grid-based visual encoding methods take fragmented features extracted from the entire image as input, lacking the fine-grained semantic information ...

Adaptive decoupling-fusion in Siamese network for image classification.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) are highly regarded for their ability to extract semantic information from visual inputs. However, this capability often leads to the inadvertent loss of important visual details. In this paper, we introduce an Ad...

A spatial-spectral fusion convolutional transformer network with contextual multi-head self-attention for hyperspectral image classification.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) can effectively extract local features, while Vision Transformer excels at capturing global features. Combining these two networks to enhance the classification performance of hyperspectral images (HSI) has garner...

Semi-supervised non-negative matrix factorization with structure preserving for image clustering.

Neural networks : the official journal of the International Neural Network Society
Semi-supervised learning methods have wide applications thanks to the reasonable utilization for a part of label information of data. In recent years, non-negative matrix factorization (NMF) has received considerable attention because of its interpre...

Dynamic semantic-geometric guidance and structure transfer network for cross-scene hyperspectral image classification.

Neural networks : the official journal of the International Neural Network Society
Recently, cross-scene hyperspectral image classification(HSIC) via domain adaptation is drawing increasing attention. However, most existing methods either directly align the source domain and target domain without fully mining of SD information, or ...

Accelerated EPR imaging using deep learning denoising.

Magnetic resonance in medicine
PURPOSE: Trityl OXO71-based pulse electron paramagnetic resonance imaging (EPRI) is an excellent technique to obtain partial pressure of oxygen (pO) maps in tissues. In this study, we used deep learning techniques to denoise 3D EPR amplitude and pO m...