In this work we address the problem of real-time dynamic MRI reconstruction. There are a handful of studies on this topic; these techniques are either based on compressed sensing or employ Kalman Filtering. These techniques cannot achieve the reconstruction speed necessary for real-time reconstruction. In this work, we propose a new approach to MRI reconstruction. We learn a non-linear mapping ...

Eye detection is an important step for a range of applications such as iris and face recognition. For eye detection in practice, speed is as equally important as accuracy. In this paper, we propose a super-fast (1000 fps on a general PC) eye detection method based on the label map of the raw image without face detection. We firstly produce the label map of a raw image according to the coordinat...

An effective similarity measure for multi-modal images is crucial for medical image fusion in many clinical applications. The underlining correlation across modalities is usually too complex to be modelled by intensity-based statistical metrics. Therefore, approaches of learning a similarity metric are proposed in recent years. In this work, we propose a novel deep similarity learning method th...

In recent years, extreme weather has occurred frequently, and the risk of heavy rainfall flooding faced by people risen. It is therefore an urgent requirement to carry out applied research on assessment. We took Henan Province, where a major flood disaster in 2021, as example analyze impact factors urban conduct Indicators were first selected from population, housing, economy, correlation analy...

Data mining in the educational field can be used to optimize teaching and learning performance among students. The recently developed machine (ML) deep (DL) approaches utilized mine data effectively. This study proposes an Improved Sailfish Optimizer-based Feature Selection with Optimal Stacked Sparse Autoencoder (ISOFS-OSSAE) for pattern recognition sector. proposed ISOFS-OSSAE model aims deri...

In Bioinformatics, Protein Secondary Structure Prediction (PSSP) has been considered as one of the main challenging tasks in this field. Today, secondary structure protein prediction approaches have been categorized into three groups (Neighbor-based, model-based, and meta predicator-based model). The main purpose of the model-based approaches is to detect the protein sequence-structure by utili...