AIMC Topic: Remote Sensing Technology

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HE-DFNETS: A Novel Hybrid Deep Learning Architecture for the Prediction of Potential Fishing Zone Areas in Indian Ocean Using Remote Sensing Images.

Computational intelligence and neuroscience
The Indian subcontinent is known for its larger coastline spanning, over 8100 km and is considered the habitat for many millions of people. The livelihood of their habitat is purely dependent upon the fishing activities. Often, the search for fish re...

Optimization of Sample Construction Based on NDVI for Cultivated Land Quality Prediction.

International journal of environmental research and public health
The integrated use of remote sensing technology and machine learning models to evaluate cultivated land quality (CLQ) quickly and efficiently is vital for protecting these lands. The effectiveness of machine-learning methods can be profoundly influen...

HARNU-Net: Hierarchical Attention Residual Nested U-Net for Change Detection in Remote Sensing Images.

Sensors (Basel, Switzerland)
Change detection (CD) is a particularly important task in the field of remote sensing image processing. It is of practical importance for people when making decisions about transitional situations on the Earth's surface. The existing CD methods focus...

Detection of spatial avoidance between sousliks and moles by combining field observations, remote sensing and deep learning techniques.

Scientific reports
Nowadays, remote sensing is being increasingly applied in ecology and conservation, and even underground animals can successfully be studied if they leave clear signs of their presence in the environment. In this work, by combining a field study, ana...

Extracting Wetland Type Information with a Deep Convolutional Neural Network.

Computational intelligence and neuroscience
Wetlands have important ecological value. The application of wetland remote sensing is essential for the timely and accurate analysis of the current situation in wetlands and dynamic changes in wetland resources, but high-resolution remote sensing im...

Land Resource Use Classification Using Deep Learning in Ecological Remote Sensing Images.

Computational intelligence and neuroscience
Aiming at the problems that the traditional remote sensing image classification methods cannot effectively integrate a variety of deep learning features and poor classification performance, a land resource use classification method based on a convolu...

Detection of plane in remote sensing images using super-resolution.

PloS one
The object detection of remote sensing image often has low accuracy and high missed or false detection rate due to the large number of small objects, instance level noise and cloud occlusion. In this paper, a new object detection model based on SRGAN...

Root-zone soil moisture estimation based on remote sensing data and deep learning.

Environmental research
Soil moisture in the root zone is the most important factor in eco-hydrological processes. Even though soil moisture can be obtained by remote sensing, limited to the top few centimeters (<5 cm). Researchers have attempted to estimate root-zone soil ...

AGs-Unet: Building Extraction Model for High Resolution Remote Sensing Images Based on Attention Gates U Network.

Sensors (Basel, Switzerland)
Building contour extraction from high-resolution remote sensing images is a basic task for the reasonable planning of regional construction. Recently, building segmentation methods based on the U-Net network have become popular as they largely improv...

Fuzzy Cognitive Maps with Bird Swarm Intelligence Optimization-Based Remote Sensing Image Classification.

Computational intelligence and neuroscience
Remote sensing image (RSI) scene classification has become a hot research topic due to its applicability in different domains such as object recognition, land use classification, image retrieval, and surveillance. During RSI classification process, a...