Add to ORKGNational audienceIn this paper, first, we present the problem of Non Cooperative Target Recognition (NCTR) as a supervised classification problem. Then, we use a very simple method of K Nearest Neighbors (KNN) to do this classification. We explore and compare the performances of this algorithm based on the choice of the distances and the representation spaces of the data. KNN algorithm will be executed initially on CPU with Matlab and then on GPU using MEX functions of Matlab. Time computing and memory transfert time will be taken into account to evaluate the benefit of such an implementation
Nearest neighbor (NN) techniques are commonly used in remote sensing, pattern recognition and statis...
Abstract The nearest neighbour (NN) classification rule is usuallychosen in a large number of patter...
Abstractk-Nearest Neighbor (k-NN) classification technique is one of the most elementary and straigh...
Dans cet article, nous nous sommes intéressés aux problèmes de reconnaissance non- coopérative de ci...
National audienceIn this paper, first, we present the problem of Non Cooperative Target Recognition ...
The main subject of this thesis is the study of algorithms for non-cooperative targets recognition (...
Le thème principal de cette thèse est l'étude d'algorithmes de reconnaissance de cibles non coopérat...
The k--Nearest Neighbor algorithm (k-NN) uses a classification criterion that depends on the parame...
In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects ...
The typical nonparametric method of pattern recognition "k-nearest neighbor rule (kNN)" is carried o...
The k-NN classifier is one of the most known and widely used nonparametric classifiers. The k-NN rul...
k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametri...
This thesis is related to distance metric learning for kNN classification. We use the k nearest neig...
k nearest neighbor (kNN) is an effective and powerful lazy learning algorithm, notwithstanding its e...
Abstract: The k-Nearest Neighbor (k-NN) is very simple and powerful approach to conceptually approxi...
Nearest neighbor (NN) techniques are commonly used in remote sensing, pattern recognition and statis...
Abstract The nearest neighbour (NN) classification rule is usuallychosen in a large number of patter...
Abstractk-Nearest Neighbor (k-NN) classification technique is one of the most elementary and straigh...
Dans cet article, nous nous sommes intéressés aux problèmes de reconnaissance non- coopérative de ci...
National audienceIn this paper, first, we present the problem of Non Cooperative Target Recognition ...
The main subject of this thesis is the study of algorithms for non-cooperative targets recognition (...
Le thème principal de cette thèse est l'étude d'algorithmes de reconnaissance de cibles non coopérat...
The k--Nearest Neighbor algorithm (k-NN) uses a classification criterion that depends on the parame...
In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects ...
The typical nonparametric method of pattern recognition "k-nearest neighbor rule (kNN)" is carried o...
The k-NN classifier is one of the most known and widely used nonparametric classifiers. The k-NN rul...
k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametri...
This thesis is related to distance metric learning for kNN classification. We use the k nearest neig...
k nearest neighbor (kNN) is an effective and powerful lazy learning algorithm, notwithstanding its e...
Abstract: The k-Nearest Neighbor (k-NN) is very simple and powerful approach to conceptually approxi...
Nearest neighbor (NN) techniques are commonly used in remote sensing, pattern recognition and statis...
Abstract The nearest neighbour (NN) classification rule is usuallychosen in a large number of patter...
Abstractk-Nearest Neighbor (k-NN) classification technique is one of the most elementary and straigh...