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Vision — based road lane detection and reconstruction is a very common interest in the field of computer vision (CV). It has numerous application ranging from autonomous vehicle to driver assist and support systems technology. These researches are always focusing on both accuracy and complexity of the system's output; however, none of these uses Macro Block (MB) method. This paper introduces the characteristics...
Node Localization is the major challenge in Wireless Sensor network. The presence of measurement error and noise in the environment makes process of localization more erroneous and complicated. In this paper LLE-Isomap based manifold learning algorithm is used to solve the problem of node localization. Results of LLE-Isomap is compared with various others manifold learning algorithms like MDS, Isomap,...
One goal of Virtual Analog modeling of audio circuits is to produce digital models whose behavior matches analog prototypes as closely as possible. Discretization methods provide a systematic approach to generate such models but they introduce frequency response error, such as frequency warping for the trapezoidal method. Recent work showed how using different discretization methods for each reactive...
Contrast is a very important characteristic for visual perception of image quality. Some No-Reference Image Quality Assessment Algorithm NR-IQA metrics for Contrast-Distorted Images (CDI) have been proposed in the literature, e.g. Reduced-reference Image Quality Metric for Contrast-changed images (RIQMC) and NR-IQA for Contrast-Distorted Images (NR-IQACDI). Here, we intend to improve the assessment...
Electrophysiological data processing can take place both in time and in frequency domains as well as in the joint time-frequency domain. Short Time Fourier Transform and Wavelet Transform are commonly used time-frequency analysis methods. The limitations of these methods initiated the use of methods such as synchrosqueezing and multivariate synchrosqueezing methods. In our proposed method 88.9%, 77...
This paper proposes a lane estimation algorithm on roads where lanes are not visible due to fading or bad weather conditions. The proposed algorithm is conducted by utilizing the road width and remained lines on roads. The results indicate that the proposed algorithm can estimate lanes in heavy rains and nights.
Bent function is an important nonlinear function in design of stream cipher and S-box. More than eight variables Bent functions can only be generated by construction, up to now, most of these functions are still not found. In this paper, the Bent function search algorithm based on truth table is presented via analyzing the value distribution and run length property of the Bent function. Compared with...
In this paper we study the shape space of curves with values in a homogeneous space M = G/K, where G is a Lie group and K is a compact Lie subgroup. We generalize the square root velocity framework to obtain a reparametrization invariant metric on the space of curves in M. By identifying curves in M with their horizontal lifts in G, geodesics then can be computed. We can also mod out by reparametrizations...
Stationarity of reconstruction problems is the crux to enabling convolutional neural networks for many image processing tasks: the output estimate for a pixel is generally not dependent on its location within the image but only on its immediate neighbourhood. We expect other invariances, too. For most pixel-processing tasks, rigid transformations should commute with the processing: a rigid transformation...
Due to the randomness in time and space and unobvious characteristics, it is difficult to detect the DC arc fault. To solve the problem, this paper studies the Hilbert-Huang transform to extract the frequency domain characteristics of AC components of the current. The sum of harmonic power in the range from 20kHz to 100kHz is calculated by the IMF4 method, which can be used as the characteristic parameters...
We present a technique based on permutations, the well known arcade game Pacman, and limited-precision integers to encode data into balanced codewords. The redundancy that is introduced by the encoding is particularly low. The results are noticeably better than those of previous work. Still, the resources required by our technique remain modest: there is no need for costly calculations using large...
Based on the scale-invariant feature transform, this paper presents an approach to keyboard recognition. Not only the skewed keyboard can be corrected, but also the keys in the keyboard can be located. Experimental results confirm the feasibility of the proposed method.
System of symmetric ternary functions was brought to the new forms. Several systems of functions based on symmetric ternary functions were developed. All developed systems of functions were tested for possibility of being applied for representation of information flows using orthogonal transforms. An orthogonal system of functions based on symmetric ternary functions was developed and proved to be...
The work offers a new method for analyzing and optimizing the topologie observability of cognitive maps of complex spatially distributed systems in terms of various approaches to setting the optimization problems. Such method is based on a new criterion of optimal level of its observability. The method has been elaborated on the basis of the well-known topologic observability analysis technique applicable...
In this work, an image processing based lane-detection approach is proposed. In the proposed approach, candidate pixels that can be used for lane markings are detected by making use of 1-bit transform as a pre-processing step. Next, feature points are extracted via Sobel filter and candidate lane markings are decided employing a correlation and Hough transform based approach. Finally, Kalman filter...
Sleep scoring is performed by examining the recorded electroencephalogram (EEG) and some other signals recorded by a polysomnography (PSG) device. This process is considered more reliable as it is done manually by experts. However, due to the fact that experts may also be mistaken, it has led to an increase in the importance given to automatic sleep staging studies. Many methods have been tested on...
Research in time series (TS) knowledge discovery in general, and in similarity search in particular has been very active in recent years, due to the number of application domains that are progressively requiring to work with large amounts of high dimensional TS data. Unfortunately, for many practical applications, the high dimensionality in such frameworks makes it difficult to uncover important patterns...
This paper presents a new approach for acoustic environment classification based on the discrete Hartley transform. The approach applies a Hidden Markov Model based classifier on test data composed of audio clips, in order to determine which environment is surrounding these audio clips. The approach uses features obtained from the discrete Hartley transform, leading to a set of features that require...
Semantic image segmentation is now an exciting area of research owing to its various useful applications in daily life. This paper introduces a hierarchical joint-guided network (HJGN) which is mainly composed of proposed hierarchical joint learning convolutional networks (HJLCNs) and proposed joint-guided and making networks (JGMNs). HJLCNs exhibit high robustness in the segmentation of unseen objects...
Nowadays image manipulation plays an important role due to the powerful photo editing software such as Picasa, Photoshop so that it looks like as original. Such tampering with the original digital image is called as image forgery. The detection of image forgery in an image is important so it can be used as legal evidence in investigations such as court and other fields. Many Images are used as genuine...
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