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An optimized segmentation convolutional neural network with ...


An optimized segmentation convolutional neural network with ...

In this study, we designed a composite loss function with a dynamic weight, called Dynamic Energy Loss, for spine MR images segmentation.

An optimized segmentation convolutional neural network with ...

3D reconstruction for lumbar spine based on segmentation of Magnetic Resonance (MR) images is meaningful for diagnosis of degenerative lumbar spine diseases ...

An optimized segmentation convolutional neural network with ...

However, spine MR images with unbalanced pixel distribution often cause the segmentation performance of Convolutional Neural Network (CNN) reduced.

An optimized segmentation convolutional neural network ... - SciSpace

An optimized segmentation convolutional neural network with dynamic energy loss function for 3D reconstruction of lumbar spine MR images ... TL;DR: Wang et al. as ...

An optimized segmentation convolutional neural network ... - OUCI

An optimized segmentation convolutional neural network with dynamic energy loss function for 3D reconstruction of lumbar spine MR images · List of references.

A Novel Approach to Optimizing Convolutional Neural Networks for ...

PDF | To divide a digital image into individual parts that share similar characteristics is known as digital image segmentation, and it is a ...

A Novel Approach to Optimizing Convolutional Neural Networks for ...

To divide a digital image into individual parts that share similar characteristics is known as digital image segmentation, and it is a vital ...

Semantic Segmentation Model Optimized on a 224mW CNN ... - arXiv

The experimental result shows that the model running on the 224mW chip achieves the speed of 318FPS with excellent accuracy for applications such as person ...

Brain tumor segmentation based on optimized convolutional neural ...

Brain tumor segmentation based on optimized convolutional neural network and improved chimp optimization algorithm. Comput Biol Med. 2024 Jan:168:107723. doi ...

Optimizing the performance of convolutional neural network ... - Nature

This study investigates the optimal configuration of convolutional neural network (CNN)-based MEC by proposing an effective data segmentation technique and a ...

Brain Tumor Segmentation Based on an Optimized Convolutional ...

All weight and bias values of the CNN model are adjusted using an improved chimp optimization algorithm (IChOA). In the first step, we ...

Optimizing CNN-based Segmentation with Deeply Customized ...

In this work, we propose and develop deconvolution architecture for efficient FPGA implementation. FPGA-based accelerators are proposed for both deconvolution ...

Optimized KiU-Net: Lightweight Convolutional Neural Network for ...

Medical image segmentation helps with computer-assisted disease analysis, operations, and therapy. Blood vessel segmentation is very ...

(PDF) Medical Image Segmentation Algorithm Based on Optimized ...

The optimized convolutional neural network model can segment medical images using the features of two scales simultaneously. At the same time, ...

Application of Optimized Convolution Neural Network Model in ...

To address the problems of blurred target boundaries and inefficient image segmentation in ancient mural image segmentation, ...

Optimizing convolutional neural network segmentation tasks using ...

This thesis shows that evolutionary algorithms successfully improve state-of-the-art neural network models in image segmentation.

Image semantic segmentation system based on optimized neural ...

It must keep pace with the development and optimize the corresponding neural network algorithm. Recently, deep convolutional neural network is the main solution ...

CNN-IKOA: convolutional neural network with improved Kepler ...

This study presents an alternative image segmentation technique based on an enhanced version of the Kepler optimization algorithm (KOA), namely IKOA.

Optimized U-shape convolutional neural network with a novel ...

After the introduction of fully convolutional neural networks (FCN) as a powerful method for semantic segmentation, Dung and Anh used an FCN ...

Medical image segmentation using an optimized three-tier quantum ...

An optimized three-tier quantum convolutional neural network (O-TT-QCNN) is proposed for segmentation, which can handle complex and heterogeneous medical ...