This paper is a survey of fuzzy set theory applied in cluster analysis. These fuzzy clustering algorithms have been widely studied and applied in a variety of substantive areas. They also become the major techniques in cluster analysis. In this paper, we give a survey of fuzzy clustering in three categories. The first category is the fuzzy clustering based on fuzzy relation. The second one is t...

Classification of spatial data has become important due to the fact that there are huge volumes of spatial data now available holding a wealth of valuable information. In this paper we consider the classification of spatial data streams, where the training dataset changes often. New training data arrive continuously and are added to the training set. For these types of data streams, building a ...

With m processors available, the k-nearest neighbor classifier can be straightforwardly parallelized with a linear speed increase of factor m. In this paper we introduce two methods that in principle can achieve this aim. The first method splits the test set in m parts, while the other distributes the training set overm sub-classifiers, and merges their m nearest neighbor sets with each classif...

Conventionally, the k nearest-neighbor (kNN) classification is implemented with use of Euclidean distance-based measures, which are mainly one-to-one similarity relationships such as to lose connections between different samples. As a strategy alleviate this issue, coefficients coded by sparse representation have played role gauger for well. Although SR enjoy remarkable discrimination nature on...

This paper presents a novel type of queries in spatial databases, called the direction-aware bichromatic reverse k nearest neighbor(DBRkNN ) queries, which extend the bichromatic reverse nearest neighbor queries. Given two disjoint sets, P and S, of spatial objects, and a query object q in S, the DBRkNN query returns a subset P ′ of P such that k nearest neighbors of each object in P ′ include ...

The mechanized ability to specify the way surface type is a piece of key enlightenment for autonomous transportation machine navigation like wheelchairs and smart cars. In present work, extracted features from object are getting based on structure evidence using Gray Level Co-occurrence Matrix (GLCM). Furthermore, K-Nearest Neighbor (K-NN) Classifier was built classify road image into three cla...

Standard implementations of non-parametric classifiers have large computational requirements. Parzen classifiers use the distances of an unknown vector to all N prototype samples, and consequently exhibit O(N) behavior in both memory and time. We describe four techniques for expediting the nearest neighbor methods. replacing the linear search with a new kd tree method, exhibiting approximately ...

We present HotSpotter, a fast, accurate algorithm for identifying individual animals against a labeled database. It is not species specific and has been applied to Grevy’s and plains zebras, giraffes, leopards, and lionfish. We describe two approaches, both based on extracting and matching keypoints or “hotspots”. The first tests each new query image sequentially against each database image, ge...