Efficient ISAR image classification using MECSM representation
نویسندگان
چکیده
منابع مشابه
Enhanced and Efficient Isar Image Focusing Using the Discrete Gabor Representation in an Oversampling Scheme
Inverse synthetic aperture radar (ISAR) imaging is one of the most well-known techniques of radar target recognition. One of the most important issues in ISAR imaging is the improvement of the image smeared by a moving target. In this paper, we propose the discrete Gabor representation (DGR) in an oversampling scheme as an effective means of obtaining a well-focused ISAR image with a short calc...
متن کاملImage Classification via Sparse Representation and Subspace Alignment
Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
متن کاملEfficient Sparse Representation Classification Using Adaptive Clustering
This paper is presenting a method for an efficient face recognition algorithm based on sparse representation classification (SRC) using an adaptive K-means clustering. In the context of face recognition, SRC is implemented based on the assumption that a face image from a particular subject can be represented as a linear combination of other face images from the same subject. SRC uses a set of e...
متن کاملProvably efficient neural network representation for image classification
The state-of-the-art approaches for image classification are based on neural networks. Mathematically, the task of classifying images is equivalent to finding the function that maps an image to the label it is associated with. To rigorously establish the success of neural network methods, we should first prove that the function has an efficient neural network representation, and then design pro...
متن کاملShip ISAR Image Classification with Probabilistic Neural Network
Ship detection and classification plays a significant role in naval warfare. Inverse Synthetic Aperture Radar (ISAR) images are being used extensively for feature extraction in ship detection and classification. The classification problem is solved in two steps. The first step is the extraction of features that characterize the target. The second step is to feed the computed feature values to a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of King Saud University - Computer and Information Sciences
سال: 2018
ISSN: 1319-1578
DOI: 10.1016/j.jksuci.2016.07.004