Stamps extraction using local adaptive k- means and ISODATA algorithms

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

Adaptive K-Means Clustering For Improving Non- Local Means Filtering

Recording devices whether analog or digital, have traits which make them susceptible to noise. In selecting a noise reduction algorithm, one must weigh several factors. Image denoising is defined as a method to recover a true image from an observed noisy image and is applied in display systems to improve the quality of image. One of the popular denoising methods, NLM, produces the quality of im...

segmentation of photospheric solar images by using c-means,k-means, and fcm algorithms

Increasing the Accuracy of Recommender Systems Using the Combination of K-Means and Differential Evolution Algorithms

Recommender systems are the systems that try to make recommendations to each user based on performance, personal tastes, user behaviors, and the context that match their personal preferences and help them in the decision-making process. One of the most important subjects regarding these systems is to increase the system accuracy which means how much the recommendations are close to the user int...

Designing an Algorithm for Cancerous Tissue Segmentation Using Adaptive K-means Cluttering and Discrete Wavelet Transform

Background: Breast cancer is currently one of the leading causes of death among women worldwide. The diagnosis and separation of cancerous tumors in mammographic imagesrequire accuracy, experience and time, and it has always posed itself as a major challenge to the radiologists and physicians. Objective: This paper proposes a new algorithm which draws on discrete wavelet transform and adaptive ...