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This study achieves greater prediction stability and model focus on important visual elements by using CNN architectures such as U-Net and ResNet, which are well-known for their efficacy in medical ...

Abstract: This paper proposes a joint multi-task learning algorithm to better predict attributes in images using deep convolutional neural networks (CNN). We consider learning binary semantic ...

Materials and Methods The Python ... image processing and sequence prediction tasks. It uses precision, recall, F1-score and accuracy in the evaluation of the proposed deep learning model. The results ...

Through image preprocessing ... Neural Network (CNN) and Long Short-Term Memory Neural Network (LSTM) was proposed. Through the preprocessing of input parking space data, time vector transformation, ...

This repo implements the following paper: Tsourounis, D.; Kastaniotis, D.; Theoharatos, C.; Kazantzidis, A.; Economou, G. SIFT-CNN: When Convolutional Neural Networks ...

The proposed explanation-driven DL model for prediction of brain tumour status using MRI image data: 2870 MRI images are pre-processed and divided into training, validation, and test sets. Two copies ...