AIMC Topic: Neural Networks, Computer

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Efficient Spiking Neural Networks with Biologically Similar Lithium-Ion Memristor Neurons.

ACS applied materials & interfaces
Benefiting from the brain-inspired event-driven feature and asynchronous sparse coding approach, spiking neural networks (SNNs) are becoming a potentially energy-efficient replacement for conventional artificial neural networks. However, neuromorphic...

Improved modeling of human vision by incorporating robustness to blur in convolutional neural networks.

Nature communications
Whenever a visual scene is cast onto the retina, much of it will appear degraded due to poor resolution in the periphery; moreover, optical defocus can cause blur in central vision. However, the pervasiveness of blurry or degraded input is typically ...

Shallow and deep learning classifiers in medical image analysis.

European radiology experimental
An increasingly strong connection between artificial intelligence and medicine has enabled the development of predictive models capable of supporting physicians' decision-making. Artificial intelligence encompasses much more than machine learning, wh...

Latent Graph Representations for Critical View of Safety Assessment.

IEEE transactions on medical imaging
Assessing the critical view of safety in laparoscopic cholecystectomy requires accurate identification and localization of key anatomical structures, reasoning about their geometric relationships to one another, and determining the quality of their e...

Slim UNETR: Scale Hybrid Transformers to Efficient 3D Medical Image Segmentation Under Limited Computational Resources.

IEEE transactions on medical imaging
Hybrid transformer-based segmentation approaches have shown great promise in medical image analysis. However, they typically require considerable computational power and resources during both training and inference stages, posing a challenge for reso...

Wavelet-Improved Score-Based Generative Model for Medical Imaging.

IEEE transactions on medical imaging
The score-based generative model (SGM) has demonstrated remarkable performance in addressing challenging under-determined inverse problems in medical imaging. However, acquiring high-quality training datasets for these models remains a formidable tas...

Evaluation and estimation of compressive strength of concrete masonry prism using gradient boosting algorithm.

PloS one
The compressive strength (CS) of the hollow concrete masonry prism is known as an important parameter for designing masonry structures. In general, the CS is determined using laboratory tests, however, laboratory tests are time-consuming and high-cos...

From CNN to Transformer: A Review of Medical Image Segmentation Models.

Journal of imaging informatics in medicine
Medical image segmentation is an important step in medical image analysis, especially as a crucial prerequisite for efficient disease diagnosis and treatment. The use of deep learning for image segmentation has become a prevalent trend. The widely ad...

Systematic Review of Retinal Blood Vessels Segmentation Based on AI-driven Technique.

Journal of imaging informatics in medicine
Image segmentation is a crucial task in computer vision and image processing, with numerous segmentation algorithms being found in the literature. It has important applications in scene understanding, medical image analysis, robotic perception, video...

Pan-cancer image segmentation based on feature pyramids and Mask R-CNN framework.

Medical physics
BACKGROUND: Cancer, a disease with a high mortality rate, poses a great threat to patients' physical and mental health and can lead to huge medical costs and emotional damage. With the continuous development of artificial intelligence technologies, d...