Results 11 to 20 of about 8,230,666 (286)

An attention-based U-Net for detecting deforestation within satellite sensor imagery [PDF]

International Journal of Applied Earth Observations and Geoinformation, 2022
In this paper, we implement and analyse an Attention U-Net deep network for semantic segmentation using Sentinel-2 satellite sensor imagery, for the purpose of detecting deforestation within two forest biomes in South America, the Amazon Rainforest and ...
David John, Ce Zhang
doaj   +5 more sources

ASCU-Net: Attention Gate, Spatial and Channel Attention U-Net for Skin Lesion Segmentation

Diagnostics, 2021
Segmentation of skin lesions is a challenging task because of the wide range of skin lesion shapes, sizes, colors, and texture types. In the past few years, deep learning networks such as U-Net have been successfully applied to medical image segmentation
Xiaozhong Tong, Junyu Wei, Bei Sun, Shaojing Su, Zhen Zuo, Peng Wu   +5 more
doaj   +2 more sources

FCD-AttResU-Net: An improved forest change detection in Sentinel-2 satellite images using attention residual U-Net

International Journal of Applied Earth Observations and Geoinformation, 2023
Forest Change Detection (FCD) is a critical component of natural resource monitoring and conservation strategies, enabling informed decision-making. Various methods utilizing the power of artificial intelligence (AI) have been developed for detecting and
Kassim Kalinaki, Owais Ahmed Malik, Daphne Teck Ching Lai   +2 more
doaj   +2 more sources

Comparison of U-Net and Attention U-Net for Binary Flood Segmentation from UAV Imagery

Journal of Applied Informatics and Computing
Flood disasters consistently cause massive damage every year, making rapid mapping of affected areas crucial for coordinating emergency aid. The use of unmanned aerial vehicles (UAVs) offers a practical solution to obtain high-resolution aerial imagery ...
Fariida Aini, Muhammad Akrom, Gustina Alfa   +2 more
doaj   +2 more sources

TransU-Net++: Rethinking attention gated TransU-Net for deforestation mapping

International Journal of Applied Earth Observations and Geoinformation, 2023
Deforestation has become a major cause of climate change, and as a result, both characterizing the drivers and estimating segmentation maps of deforestation have piqued the interest of researchers. In the computer vision domain, Vision Transformers (ViTs)
Ali Jamali, Swalpa Kumar Roy, Jonathan Li, Pedram Ghamisi   +3 more
doaj   +2 more sources

Color and Attention for U : Modified Multi Attention U-Net for a Better Image Colorization [PDF]

JOIV: International Journal on Informatics Visualization
Image colorization is a tedious task that requires creativity and understanding of the image context and semantic information. Many models have been made by harnessing various deep learning architectures to learn the plausible colorization.
Oliverio Theophilus Nathanael, Simeon Yuda Prasetyo   +1 more
doaj   +2 more sources

MSP U-Net: Crack Segmentation for Low-Resolution Images Based on Multi-Scale Parallel Attention U-Net

Applied Sciences
As the expected lifespans of structures and road approaches, as well as the importance of road maintenance, increase globally, safety inspections have emerged as a crucial task.
Joon-Hyeok Kim, Ju-Hyeon Noh, Jun-Young Jang, Hee-Deok Yang   +3 more
doaj   +2 more sources

An Automatic Nuclei Image Segmentation Based on Multi-Scale Split-Attention U-Net

, 2021
Nuclei segmentation is an important step in the task of medical image analysis. Nowadays, deep learning techniques based on Convolutional Neural Networks (CNNs) have become prevalent methods in nuclei segmentation.
Wenting Duan (17157046), Qing Xu (17924819)   +1 more
core   +5 more sources

Attention-augmented U-Net (AA-U-Net) for semantic segmentation

Signal, Image and Video Processing, 2022
Deep learning-based image segmentation models rely strongly on capturing sufficient spatial context without requiring complex models that are hard to train with limited labeled data. For COVID-19 infection segmentation on CT images, training data are currently scarce. Attention models, in particular the most recent self-attention methods, have shown to
Kumar T. Rajamani, Priya Rani, Hanna Siebert, Elagiri Ramalingam Rajkumar, Mattias P. Heinrich   +4 more
openaire   +2 more sources

Automatic Pancreatic Cyst Lesion Segmentation on EUS Images Using a Deep-Learning Approach

Sensors, 2021
The automatic segmentation of the pancreatic cyst lesion (PCL) is essential for the automated diagnosis of pancreatic cyst lesions on endoscopic ultrasonography (EUS) images. In this study, we proposed a deep-learning approach for PCL segmentation on EUS
Seok Oh, Young-Jae Kim, Young-Taek Park, Kwang-Gi Kim   +3 more
doaj   +1 more source