Sharif Digital Repository

In recent years, Machine Learning models have been developed in Signal Processing, Computer Vision and Neuroscience areas. There are two categories of Machine Learning models which are supervised and unsupervised learning models. Regression and classification problems are two popular problems examples of supervised learning models. From unsupervised learning problems, we can mention the clustering problem. Support Vector Regression (SVR), Decision Tree Regression and Bagging Ensemble Regression models are some important models of the regression problem. For classification problems, we can also mention to Support Vector Classification, Decision Tree Classification, and Bagging Ensemble... 

Recognizing human actions is an important and challenging topic in computer vision, which has important applications such as video surveillance and Indexing. From a computational perspective, actions can be defined as three-dimensional patterns, in space and in time which can be modeled using several representations. Action representations differ in visual information used in spatial dimensions (e.g., shape or appearance) and the representation of dynamics in time. The goal of this thesis is to develop new techniques and improve current results in action categorization. As such, using a general structure, three methods are proposed. In this structure, local spatio-temporal features are... 

Image retrieval refers to the task of finding images related to a query image within an image set. Due to ever-increasing volumes of data, it has become increasingly necessary to find suitable and efficient methods for searching in massive databases. In this thesis, modern image retrieval techniques developed within the last 15 years have been studied, with an aim to satisfy three primary constraints of efficiency, accuracy, and low memory usage. Our focus has been on content-based retrieval; meaning that instead of using text and other information, we directly utilize image features for analysis and processing. To achieve this, we studied two established techniques, the bag-of-words model,... 

Searching for images of the same object or scene in a large number of images is a major problem in computer vision. It has many applications specially in the search engines.For the goal of efficient image search, we need descriptors that are not only discriminative, but also short and need small amount of memory.In this thesis we analyze the image search methods in two categories: The first methods are based on converting the existed descriptors such as gist into a compact binary code. The second methods are based on building short descriptors, especially by some modifications in the framework of bag of features descriptor.Finally we will introduce a novel descriptor "bag of codes" which... 

Human activity recognition is an important and useful area in computer vision that application include surveillance systems, patient monitoring systems, human-computer interaction and analyse video data from big websites.Traditional Human action recognition use the RGB videos as default input that unable describe motion and action as full. On the other hand Kinect camera sendsthe RGB data to output in addition to the Depth Data that allows us to extract skeleton of human easily. Recently Space-time features have been particulary popular in RGB Videos because of their structure. These features are describedby their descriptor and send the good and important information to output.Finally we... 

Online voltage stability assessment is essential for preventing the failure in power systems. Voltage instability in power systems usually occurs in consequence of contingency situations or continuous load increasing or both of them. A new method for online voltage stability assessment using the data acquired from phasor measurement units (PMUs) and offline trained decision trees is presented in this thesis. The index of voltage stability margin (VSM) is used for security assessment and considering WSCC criterion, different operation points are divided in two classes: safe and unsafe. In order to obtain the voltage stability margin and generate the database, a new method which has been named... 

In content based image retrieval, low level features are used to find similar image. To do this, many system has been proposed by other people, in which in many of them, combination of features in the same time are used as a step of retrieval to increase accuracy. Feature combination are divied in two category: vector based and weight based which in weight based approach, features can get different weight, based on their importance and role in retrieval accuracy. Each image contain different partition, which some of them like background, base on their lower discrimintivity power, have lower importance. Based on our study, some image have powerfull color features and some of them have... 

Simultaneous development of technology and social networks and universal access to them caused to produce and distribute huge volume of videos that recognition of their content without use of machine vision is very hard. This thesis examine some video classification algorithms to improve them. The algorithm that is used to improve is based on one of local descriptor algorithms. At first with using STIP tools, the local interest point found by Harris3d and describe by HOG/HOF. Then by using Bag of Features, all local descriptors in a video produce a descriptor per videos. Bag of Features divide the domain of all local descriptors from all videos to K cluster and produce a vector per video... 

Physiotherapy is a major part of the rehabilitation process that is used to retrieve patients' physical ability. The recuperation feedback in the physiotherapy process has a twofold significance for both physiotherapists and patients. It helps patients regain their ability to recover more quickly, prevent recurrence of injury to the treated area and other areas, and motivate the patient to continue treatment. It also helps the physiotherapist to monitor the process of rehabilitation and ensure the correctness of the procedure. Meanwhile, many patients cannot maintain continuous workouts due to lack of access to the physiotherapist at home and inability to provide required feedback.In this... 

Cardiovascular diseases are very common nowadays and are one of the main reasons of death. Being among the major types of these diseases, correct and in time diagnosis of Coronary Artery Disease (CAD) is very important. The best and most accurate CAD diagnosis method by now is recognized as Angiography, which has many side effects and is costly. Thus researchers are seeking for inexpensive, though still accurate, methods. Existing studies have used several features in collecting data from patients, while applying different data mining algorithms to increase accuracy. In this thesis, a data set is introduced which utilizes several new and effective features for CAD diagnosis, as well as a... 

Scene classification is one of the most controversial fields in computer vision. It has many applications such as robot navigation and control, content-based image retrieval (CBIR), semantic organization of image databases, depth estimation and multimedia services. In fact the outcome of any classification system depends on the ability of the feature vector defined for the problem, by means of its distinguishing strength. In this research we focus on efficient feature extraction methods. In recent years, methods based on bags of features and special pyramid approach, have shown good performance in scene classification comparison to the others. So we based our proposed method on these ideas.... 

Today, with the development of financial and economic sciences and the increasing volume of financial data, it is necessary to process and analyze this field more accurately with up-to-date tools. On the other hand, by the significant growth of the use of machines and computers for analysis and forecasting purposes, their importance and application have been well defined. Therefore, this research is considered to provide a more efficient method by processing historical data and analyzing them using data mining techniques. The results of this study can be provided to experts in this field as an effective method. Therefore, in this research, a new method based on the selection of required...