Scientific Research Publishing

Polyp Segmentation Network with Dual-Decoder Pyramid Visual Converter ()

To address the challenges of morphological irregularity and boundary ambiguity in colorectal polyp image segmentation, we propose a Dual-Decoder Pyramid Vision Transformer Network (DDPVT-Net). This ...
IEEE

Building Precision: Efficient Encoder–Decoder Networks for Remote Sensing Based on Aerial RGB and LiDAR Data

Abstract: Precision in building delineation plays a pivotal role in population data analysis, city management, policy making, and disaster management. Leveraging computer vision technologies, ...
IEEE

Applications of Deep Learning Models on the Medical Images of Osteonecrosis of the Femoral Head (ONFH): A Comprehensive Review

Abstract: Deep learning models have demonstrated promising results in the early and accurate diagnosis of osteonecrosis of the femoral head (ONFH), enabling early detection and informed surgical ...
GitHub

The repository contains the network and the related scripts for encoder-decoder based Chemical Image Recognition

This can be done using pip, check the Tensorflow website for the installation guide. DECIMER can run on both CPU and GPU platforms. Installing Tensorflow-GPU should be done according to this guide.
The Lancet

Predicting sepsis using deep learning across international sites: a retrospective development and validation study

When sepsis is detected, organ damage may have progressed to irreversible stages, leading to poor prognosis. The use of machine learning for predicting sepsis early has shown promise, however ...
C&EN

Deep Learning for Operating Performance Assessment of Industrial Processes with Layer Attention-Based Stacked Performance-Relevant Denoising Auto-Encoders

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...
Frontiers

Longitudinal detection of new MS lesions using deep learning

The detection of new multiple sclerosis (MS) lesions is an important marker of the evolution of the disease. The applicability of learning-based methods could automate this task efficiently. However, ...