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Hyperspectral imaging provides new chances for face recognition by improved discrimination in the spectral dimension. In this paper, we investigate hyperspectral face recognition by studying twenty-four existing 2D face recognition methods in ...

In this paper, we perform a systematical study on existing 2D denoising methods for reducing the noise in magnetic resonance imaging (MRI). We conduct experiments on six MRI images with the following denoising methods: wiener2, wavelet-based ...

Denoising convolutional neural networks (DnCNN) has been proposed recently for image denoising for additive white Gaussian noise with both blind and non-blind versions. For blind DnCNN, the networks are trained with noise levels from 0 to 55, ...

• Different datasets are utilized to learn segment complex background information.

Automatic weed control using weeding robots has arisen as a promising alternative for reducing the amount of herbicide applied in the agriculture and landscaping industry. Dandelion detection is a challenging task for weeding robots. ...

In this paper, we conduct a study for the effects of principal component analysis (PCA) on hyperspectral imagery denoising. Our previous works combined PCA with wavelet shrinkage, block matching and 3D filtering (BM3D), and block matching and 4D ...

Face recognition under varying illumination is a difficult problem in many real-life applications. Various methods have been developed in the literature to deal with this problem. In this paper, we propose a new method for face recognition under ...

This paper presents an adaptive multi-tracker optimization algorithm (AMTOA) for global optimization problems with an emphasis on applications in chemical engineering. To obtain the AMTOA, first, several modifications are performed on the ...${}_{}$${}_{}$${}_{}$$$${}_{}$

Hyperspectral face recognition plays an important role in remote sensing. However, it faces many challenges such as difficulty in data acquisition, low signal to noise ratio (SNR), and high dimensionality. In this paper, we develop a novel method ...

Applications of Unmanned Aircraft Systems (UAS) are growing fast in many areas, including Advanced Air Mobility (AAM) which requires the safe integration of aerial vehicles in an airspace that is shared by many other operators. Autonomous or automated UAS ...

In this paper, we propose a novel algorithm for hyperspectral image (HSI) classification. We use locally linear embedding (LLE) to reduce the dimensionality of the data cube, 2D spatial filtering on the LLE output band images, and support vector ...

Endmember extraction is widely used to detect spectrally unique signatures of pure ground materials in hyperspectral imagery (HSI). In this paper, we study which method is good for reducing the dimensionality of the input data cubes for endmember ...

The parallel robots exhibit some outstanding properties on the repeatability, stiffness and force-to-weight ratio compared with serial robots. 6-DOF parallel robots have been utilized in various applications and the research on control design has ...

Face recognition under varying lighting conditions is an important topic in many real-life applications. In this paper, we propose a novel algorithm for illumination invariant face recognition. We first convert the face images to the logarithm ...

In this paper, a novel identification scheme is proposed for a class of singularly perturbed nonlinear systems. In order to identify the unknown singularly perturbed nonlinear system, a set of filtered variables are firstly defined and incorporated into ...

The accuracy and stability are two fundamental concerns of the visual servoing control system. This paper presents an enhanced image based visual servoing (IBVS) method which can increase the accuracy of visual servoing with guaranteed stability. The ...

The adaptive optimal control of unknown nonlinear system with different time scales is considered in this paper. The commonly used singular perturbation theory (SPT) to solve this problem is based on the accurately reduced system model, which is ...

This paper deals with the robust adaptive observer design for nonlinear dynamic systems that have an underlying multiple time-scales structure via different time-scales neural network. The Lyapunov function method is used to develop a novel stable ...

Visual control of manipulators provides significant advantages when working with targets with unknown positions. Among all visual servoing categories, the stereo visual servoing has shown to be very effective when dealing with unstructured environments. ...

This paper applies two Neural Network (NN)-based image features Zhao et al. (2012) to solve the problem of decoupling the rotational velocities around x and y axes of camera frame in robotic visual servoing systems. Based on these two image features and ...

This paper deals with adaptive nonlinear identification and trajectory tracking problem via dynamic multilayer neural network with different time scales. By means of a Lyapunov-like analysis, we determine stability conditions for the on-line ...