in this paper, we present a new brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (ls-svm). the method consists of three steps. in the first two steps, the skull is removed and cerebrospinal fluid (csf) is extracted. these two steps are performed using the fast toolbox (fmrib's a...

اساس برنامه‌ریزی و مدیریت صحیح داشتن آمار اطلاعات دقیق به‌هنگام است. یکی از مهم‌ترین بخش کشاورزی میزان تولید سالیانة هر محصول یا سطح زیرکشت ابزارهایی که در کمترین زمان با هزینة پایین دقت مناسب، می‌تواند محصولات را محاسبه کند دانش فنّاوری سنجش ‌از دور این تحقیق، دو روش طبقه‌بندی شبکة عصبی مصنوعی ماشین بردار پشتیبان استفاده‌ شده غالب منطقه، شامل هشت کلاس، تصاویر سری زمانی سنتینل‌ـ2 برآورد براساس ن...

Learning ranking (or preference) functions has become an important data mining task in recent years, as various applications have been found in information retrieval. Among rank learning methods, ranking SVM has been favorably applied to various applications, e.g., optimizing search engines, improving data retrieval quality. In this paper, we first develop a 1-norm ranking SVM that is faster in...

Assume a teacher provides examples one by one. An approximate incremental SVM computes a sequence of classi ers that are close to the true SVM solutions computed on the successive incremental training sets. We show that simple algorithms can satisfy an averaged accuracy criterion with a computational cost that scales as well as the best SVM algorithms with the number of examples. Finally, we ex...

This paper presents a study of employing Ranking SVM and Convolutional Neural Network for two missions: legal information retrieval and question answering in the Competition on Legal Information Extraction/Entailment. For the first task, our proposed model used a triple of features (LSI, Manhattan, Jaccard), and is based on paragraph level instead of article level as in previous studies. In fac...

This paper describes the ITNLP system participated in the Knowledge Base Population (KBP) track English Entity Linking task. Our Entity linking system is composed of three parts: candidate generation, candidate ranking and nil clustering. In the candidate generation process, the redirect pages and anchor texts in Wikipedia are utilized to generate candidate entities for the mentions. Ranking SV...

Outlier detection is an important task in data mining because outliers can be either useful knowledge or noise. Many statistical methods have been applied to detect outliers, but they usually assume a given distribution of data and it is difficult to deal with high dimensional data. The Statistical Learning Theory (SLT) established by Vapnik et aI. provides a new way to overcome these drawbacks...