Interest point approaches that extract local features from images are commonly used in human action recognition field. In this paper, a comparison study is performed in which different interest point approaches are used. Each approach is discussed with its advantages and drawbacks. Common keypoints extractor like scale invariant features transform (SIFT), speeded up robust features (SURF), etc....

The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components. This problem is challenging due to the large variations of features of these components (size, shape, orientation or texture). In this paper we present an automatic technique to robustly delimit the epithelial area (crypts) in microscopic images taken from colon tissues section...

A new two-parameter model is proposed using the Kavya–Manoharan (KM) transformation family and Burr X (BX) distribution. The called Kavya–Manoharan–Burr (KMBX) model. statistical properties are obtained, involving quantile (QU) function, moment (MOs), incomplete MOs, conditional MO-generating entropy. Based on simple random sampling (SiRS) ranked set (RaSS), parameters estimated via maximum lik...

بخش اورژانس یکی از شلوغ‌ترین بخش‌های یک بیمارستان است و بهبود عملکرد این تأثیر بسیاری در کیفیت ارائه خدمات دارد. اخیراً پژوهشگران به­‌دلیل تمرکز مهندسی تاب‌آوری مدیریت ناب بر کارایی سیستم‌ها توجه بسیار زیادی به دو دیدگاه کنار یکدیگر داشته‌اند. هدف پژوهش، رویکردی یکپارچه برای ارزیابی مبتنی شاخص‌های با ارتقای رضایت شغلی کاهش هزینه‌های درمانی واحد خصوصی است. منظور، ابتدا شناسایی مؤثر، مدل مفهومی مس...

Visual identification of complex images (e.g. images of food) remains a challenging problem. In particular, contentbased visual information retrieval (CBVIR) methods, which seem a natural choice for such tasks, are often constrained by specific characteristics of the images of interest and (possibly) other practical requirements. In this paper, a novel CBVIR approach to automatic food identific...