Abstract: The quantitative evaluation of defects is one of the challenges of eddy current (EC) testing. Efficient algorithm that requires a small amount of time and hardware resources is needed. In ...
Abstract: In recent years, FPGA-based convolutional neural networks (CNNs) accelerator has received tremendous research interest, especially in fields such as autonomous driving and robotics. For the ...
In tackling the intricate task of predicting brain age, researchers introduce a groundbreaking hybrid deep learning model that integrates Convolutional Neural Networks (CNN) and Multilayer Perceptron ...
error in inference process (no valid convolution algorithms available in CuDNN) #25 ...
ABSTRACT: Spam emails pose a threat to individuals. The proliferation of spam emails daily has rendered traditional machine learning and deep learning methods for screening them ineffective and ...
Reasoning efficiently across extended sequences is a major difficulty in machine learning. Recently, convolutions have emerged as a critical primitive for sequence modeling, supporting ...
File "/workspace/miniconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv/runner/iter_based_runner.py", line 130, in run iter_runner(iter_loaders[i], **kwargs ...
Diagnosis of shockable rhythms leading to defibrillation remains integral to improving out‐of‐hospital cardiac arrest outcomes. New machine learning techniques have emerged to diagnose arrhythmias on ...
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