Several machine-learning algorithms have been proposed for remote sensing image
classification during the past two decades. Among these machine learning algorithms …

Abstract Machine learning (ML) is a field of artificial intelligence that has rapidly emerged in
molecular biology, thus allowing the exploitation of Big Data concepts in plant genomics. In …

Wind energy has seen great development during the past decade. However, wind turbine
availability and reliability, especially for offshore sites, still need to be improved, which …

Regression based methods are not performing as well as detection based methods for
human pose estimation. A central problem is that the structural information in the pose is not …

In many medical image analysis applications, only a limited amount of training data is
available due to the costs of image acquisition and the large manual annotation effort …

With the emergence of the big data age, the issue of how to obtain valuable knowledge from
a dataset efficiently and accurately has attracted increasingly attention from both academia …

Robust and fast detection of anatomical structures is a prerequisite for both diagnostic and
interventional medical image analysis. Current solutions for anatomy detection are typically …

Knee osteoarthritis (OA) is the most common musculoskeletal disease without a cure, and
current treatment options are limited to symptomatic relief. Prediction of OA progression is a …

We explore the applicability of deep convolutional neural networks (CNNs) for multiple
landmark localization in medical image data. Exploiting the idea of regressing heatmaps for …

Soil moisture content (SMC) is an important factor that affects agricultural development in
arid regions. Compared with the space-borne remote sensing system, the unmanned aerial …