* Copyright (C) 2010-2018 Arm Limited or its affiliates. All rights reserved. * SPDX-License-Identifier: Apache-2.0 * Licensed under the Apache License, Version 2.0 ...
The esp-nn optimized convolution functions are producing incorrect outputs, leading to a significant drop in model accuracy from 92% to below 70%. When using the standard ANSI C implementation, the ...
With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with ...
A Multiscale Convolution SAR Image Target Recognition Method Based on Complex-Valued Neural Networks
Abstract: Recent advances in deep learning have driven significant success in synthetic aperture radar (SAR) automatic target recognition, particularly through convolutional neural network (CNN) based ...
Convolution is used in a variety of signal-processing applications, including time-domain-waveform filtering. In a recent series on the inverse fast Fourier transform (FFT), we concluded with a ...
Abstract: Small object detection represents a pivotal sub-domain within the field of computer vision. Previous research aimed at enhancing detection accuracy has included augmenting the head layer, ...
Aiming at the problems of traditional image super-resolution reconstruction algorithms in the image reconstruction process, such as small receptive field, insufficient multi-scale feature extraction, ...
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