• Improving Loss Function for a Deep Neural Network for Lesion ...🔍
• Deep Neural Frameworks Improve the Accuracy of General ...🔍
• An Effective Deep Neural Network for Lung Lesions Segmentation ...🔍
• Toward Multicenter Skin Lesion Classification Using Deep Neural ...🔍
• Skin Lesion Classification Using Deep Neural Network🔍
• An optimized segmentation convolutional neural network with ...🔍
• An Analysis of Loss Functions for Heavily Imbalanced Lesion ...🔍
• A new imbalance|aware loss function to be used in a deep neural ...🔍

Improving Loss Function for a Deep Neural Network for Lesion ...

This paper proposes a novel method to address these limitations. We propose to improve a state-of-the-art encoder-decoder based model for image segmentation.

Improving Loss Function for a Deep Neural Network for Lesion ...

A novel method of Lung image segmentation based on Textural Echo State Neural Network is proposed in this paper. This work combines the textural features of ...

Deep Neural Frameworks Improve the Accuracy of General ...

In dermatology, image recognition using a set of algorithms called deep neural networks (DNNs) has proven to be of significant aid to physicians in the ...

An Effective Deep Neural Network for Lung Lesions Segmentation ...

Then, to improve the convergence of network, a combination loss function is introduced to lead gradient optimization and training direction.

Toward Multicenter Skin Lesion Classification Using Deep Neural ...

Recently, deep neural network-based methods have shown promising advantages in accurately recognizing skin lesions from dermoscopic images.

Skin Lesion Classification Using Deep Neural Network - arXiv

lesion classification, our approach aims to use ensemble deep neural network ... weighted loss function as the approach that result in a high increase in the ...

An optimized segmentation convolutional neural network with ...

Designing a composite loss function for CNN is an effective way to enhance the segmentation capacity, yet composition loss values with fixed weight may still ...

An Analysis of Loss Functions for Heavily Imbalanced Lesion ... - MDPI

... loss functions for deep neural networks. ... Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

A new imbalance-aware loss function to be used in a deep neural ...

The aim of this study is to develop a new imbalance-aware loss function, ie, omni-comprehensive loss, to be used in deep neural networks to overcome both ...

UCM-Net: A Lightweight and Efficient Solution for Skin Lesion ... - arXiv

... loss function with the output loss and internal stage losses. The new designed function can improve UCM-Net's learning ability. Report issue ...

Investigation of an efficient multi-modal convolutional neural network ...

The main improvement is the larger number of training samples (every slice of a volume instead of just one volume), which reduces the chance of ...

Dynamically Weighted Balanced Loss: Class Imbalanced Learning ...

Index Terms—Convolutional neural networks (CNNs), cost sensitive learning, confidence calibration, data imbalance, loss functions. I. INTRODUCTION. WITH ...

ALL-Net: Anatomical information lesion-wise loss function integrated ...

To overcome the lesion size imbalance during network training and improve the detection of small lesions, a lesion-wise loss function was ...

Enhancing Skin Lesion Detection: A Multistage Multiclass ... - MDPI

The frozen weights of the CNN developed–trained with correlated images benefited the transfer learning using the same type of images for the subclassification ...

A Novel Focal Tversky Loss Function With Improved Attention U-Net ...

A generalized focal loss function based on the Tversky index is proposed to address the issue of data imbalance in medical image segmentation and improves ...

Closing the Gap Between Deep Neural Network Modeling and ...

While a variety of loss functions have been proposed in the literature, a truly optimal loss function that maximally utilizes the capacity of neural networks ...

[D] - Have neural networks that modulate their own loss functions ...

There is surprisingly a large growing field in Neural Loss Function Search (NLFS), the search for loss functions. I expect it to gain traction ...

Improving Patch-Based Convolutional Neural Networks for MRI ...

The modified DeepMedic is only trained with patches that have approximately 50% foreground (lesion) and 50% background to solve the class imbalance problem, and ...

Deep Hybrid Convolutional Neural Network for Segmentation of ...

In this study, an improved algorithm is proposed, termed EfficientUNet++, which is developed from the U-Net model. In EfficientUNet++, the ...

Improving accuracy of convolutional neural network-based skin ...

In this paper, we proposed a CNN-based skin lesion segmentation method that uses group normalization and combined loss function to enhance the ...