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Most of molecular interactions often occur in feature regions of molecular surfaces such as convex regions, cavities or pockets. In this paper we propose a method to identify these feature regions by expanding the molecular surface to its surrounding spherical surface, that is, a 1-1 mapping is established between them. According to the expansion distance, feature regions can be determined to be concave...
This paper presents a novel method for visualizing vectors of fuzzy numbers. The proposed approach is an extension of the standard polar area diagram and can be applied to a single uncertain vector or a fuzzy weighted graph with vectors of fuzzy attributes on the vertices and/or edges. The resulting diagrams are intuitive to understand and do not require an extensive background in fuzzy set theory...
Currency recognition system is one of the fast growing research fields under image processing. This paper proposes a novel method for Indian currency recognition. Our proposed approach identifies denomination by extracting features like Center Numeral, Shape, RBI Seal, Latent Image and Micro Letter. Principal Component Analysis is used to reduce the dimensions and a similarity based classifier is...
Deep architectures have been used in transfer learning applications, with the aim of improving the performance of networks designed for a given problem by reusing knowledge from another problem. In this work we addressed the transfer of knowledge between deep networks used as classifiers of digit and shape images, considering cases where only the set of class labels, or only the data distribution,...
This paper proposes a robust minutiae based fingerprint image hashing technique. The idea is to incorporate the orientation and descriptor in the minutiae of fingerprint images using SIFT-Harris feature points. A recent shape context based perceptual hashing method has been compared against the proposed technique. Experimentally, the proposed technique has been shown to deliver better robustness against...
This paper proposes a framework based on harmonic mean normalized Laplace-Beltrami spectral descriptor for non-rigid 3D shape retrieval. A series of experiments show harmonic mean normalization is suited to classification of stretched shapes, and is robust to isometric transformation, holes, local scaling, noise, shot noise and sampling. To better distinguish among shapes with fine or rough details,...
To achieve more realistic surface design, this paper proposes a new scheme of interpolation subdivision surface, which is extended from interpolation subdivision of Bezier curve. Different from the previous interpolation subdivision schemes, the normal vectors are used to generate a circle from a triangle which results in only 3 vertices and 3 edges. This improvement not only makes a curve smooth,...
In this paper, we present a novel sparse imaging approach based on the multipole expansion of the electric field. On the example of the complex target imaging, we show that higher-order multipoles provide additional pieces of information, which help to resolve cases in which standard sparse imaging fails. Therefore, higher-order sparse processing may be a valuable tool in target classification and...
The detection of cerebral aneurysms is of a paramount importance in the prevention of intracranial sub-arachnoid hemorrhage. We propose in this paper, a complete detection scheme, consisting of two phases, to detect blobs and aneurysms in cerebral 2D-DSA images. The first classification phase extracts cerebral vasculature by means of the fusion of multiple classifiers. The second detection phase involves...
The interest point (IP) matching algorithms match the points either locally or spatially. We propose a local-spatial IP matching algorithm usable for articulated human body tracking. The local-based stage finds matched IP pairs of two reference and target IP lists using a local-feature-descriptors-based matching method. Then, the spatial-based stage recovers more matched pairs from the remaining unmatched...
In this paper, we propose a new cluster validity index (CVI) based on geometrical shape. Classic CVIs are based on a combination of separation and compactness measures and may include a measure of overlap between clusters. The proposed CVI combines measures of compactness and over-lap using n-sphere shape. We conducted experiments on several real data sets from the UCI repository and compared the...
we propose a hybrid method that integrates the minutiae and their local neighborhood information. This contribution can be seen as a validation step of the minutiae triplets matching performed in a recent algorithm: M3gl. We aim to improve the result of the minutiae triplets matching stage. The characterization of the neighborhood of each triplet is established by a unique feature vector. This descriptor...
A sketch-based query interface is proposed for retrieving 3D CAD models. The maximum distribution of normal vectors of a 3D model is computed to assist the PCA algorithm to normalize the pose of the 3D model, and then the outline views of the 3D model can be coordinated with the freehand sketches submitted by users. To retrieve the 3D models similar with the user sketches, an image similarity assessment...
State-of-the-art cosmological simulations regularly contain billions of particles, providing scientists the opportunity to study the evolution of the Universe in great detail. However, the rate at which these simulations generate data severely taxes existing analysis techniques. Therefore, developing new scalable alternatives is essential for continued scientific progress. Here, we present a dataparallel,...
Manual annotation of images is usually a mandatory task in many applications where no knowledge about the image is available. In presence of huge number of images, this task becomes very tedious and prone to human errors. In this paper, we contribute in automatic annotation of ancient manuscripts by discovering manuscript calligraphy. Ancient manuscripts count a very large number of Persian and Maghrebi...
In this paper we propose a new method for detecting object class instances based on Hough transform. Hough forests which are adapted to perform Hough transform have been efficiently used for single-class object detection. In this work we extend them using HaarHOG descriptor which is a combination of Haar wavelet and HOG descriptor. As a result, we increase the number of feature channels in Hough forests...
A combined co-vibrating vector hydrophones prototype was designed and manufactured based on the actual demand of engineering, which has a dimension of Φ54×72mm, taking on an irregular shape of a cylinder with two half ball caps on each end of the cylinder, with the working frequency band 20 ∼ 5000Hz, and the average density is 1200kg/m3. Its performance was measured in both standing wave calibrator...
The aim of this paper is to propose a system where complex affordance learning is bootstrapped through using pre-learned basic-affordances as additional inputs of the complex affordance predictors or as cues in selecting the next objects to explore during learning. In the first stage, the robot learns affordances in the form of developing classifiers that predict effect categories given object features...
In this paper, we propose a distance-based control law for acyclic persistent formations of mobile agents. The proposed normalized gradient law, which can be implemented distributively by using local measurements, allows agents to achieve their desired formation shape specified by inter-agent distance constraints in finite time, with local but not global con-vergence. We show some local finite-time...
A space vector based bang-bang controller driving a rotating target system (space vector bang-bang controller with flux related hysteresis shape SVBF) such as a machine or an ac-power-supply is discussed in this paper. A two-level, three-phase conventional inverter is used as means of power conversion. The advantages such as a low switching frequency as well as further opportunities of the SVBF are...
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