Event-based cameras are bio-inspired vision sensors that mimic the sparse and asynchronous activation of the animal retina, offering advantages such as low latency and low computational load in ...
Abstract: The convolution modulation jamming method based on noise template has received widespread attention and application due to its advantages such as having the ability to obtain synthetic ...
Abstract: Convolutional neural network (CNN) quantization is an efficient model compression technique primarily used for accelerating inference and optimizing resources. However, existing methods ...
Personalized dosimetry with high accuracy is crucial owing to the growing interests in personalized medicine. The direct Monte Carlo simulation is considered as a state-of-art voxel-based dosimetry ...
When classifying hyperspectral images, 3D-CNN and 2D-CNN are limited in their application due to excessive consumption of computing resources and difficulty in effectively extracting image features.
A new brain-inspired AI method called Lp-Convolution enhances image recognition by dynamically reshaping CNN filters, combining biological realism with improved performance and efficiency. Credit: ...
Abstract: Image deblurring is a task with multiple real-world use cases. Convolutional Neural Network-based approaches to this task learn priors that generalize well to large-scale data. However, ...
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
We expect the AI age will be (almost) no-coding-programming, http://dx.doi.org/10.13140/RG.2.2.13314.66246 and http://dx.doi.org/10.13140/RG.2.2.35125.04321, whatever ...
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