Sharif Digital Repository

Most of the existing visual SLAM methods heavily rely on a static world assumption and easily fail in dynamic environments. One solution is to eliminate the influence of dynamic objects by introducing deep learning-based semantic information to SLAM systems. In this project, we propose a real-time semantic RGB-D SLAM (built upon RTAB-Map) system for dynamic environments that is capable of detecting moving objects and maintaining a static map for robust camera tracking. Furthermore, we augment the semantic segmentation process using an Extended Kalman filter module to detect temporarily static moving objects by adding centroids to each found dynamic object and calculating their velocity. We... 

Underground reservoirs are highly complicated due to the presence of spatial heterogeneities at length scales that span from micrometer in pore structure of the rocks to kilometer in the reservoir models. While large-scale flow units need to be characterized using seismic and well data, detailed displacements of fluids in pore space need to be modeled using thin section analysis and pore network modeling. It is therefore necessary to adopt a multi-scale approach to reservoir description to make best use of all the available data that vary over several orders of magnitude, from micro-scale in pore structure to field scale in reservoir flow models. In this thesis, an integrated framework for... 

In this study a mathematical model for intravitreal injection and depositing controlled release systems in the eye to treat posterior segment deseases is developed. The effects of important parameters that play a critical role in drug distribution are also studied.
Geometrical model is constructed using COMSOL software and governing equations for a 3-D model of drug distribution are solved by finite element method. The geometry is based on the exact dimensions of human eye and retina, choroid and sclera are considered separately. Choroidal losses to the circulatory system and active transport by the retinal pigment epithelium are incorporated as well. Moreover, two types of implant... 

Level set methods (LSM) are a conceptual framework for using level sets as a tool for numerical analysis of surfaces and shapes. The advantage of the level set model is that one can perform numerical computations involving curves and surfaces on a fixed Cartesian grid without having to parameterize these objects (this is called the Eulerian approach). Also, the level set method makes it very easy to follow shapes that change topology, for example when a shape splits in two, develops holes, or the reverse of these operations. All these make the level set method a great tool for modeling time-varying objects, like inflation of an airbag, or a drop of oil floating in water  

Improvement of automatic speech recognition systems and the growth of audio data (such as broadcast news, voice mail, telephony conversations and meetings) have attracted plenty of research interest in the field of speech summarization. The goal of this dissertation is to improve the performance of the speech summarization in the domain of multi-party conversations, specifically meetings. Most of the previous work in this field are inheritted from the text summarization counterpart, whithout paying much attention to the discourse specific information of the multi-party conversations. The main idea of this work is to use discourse information to improve the accuracy of extracted summaries in... 

The aim of this thesis is to investigate recent methods for Image Processing(Any signal process which it’s input is an image and it’s ouput is an image or a set of Image parameters) using Calculus of variation tools. Methods which are to be investigated has been divided into two well known parts of Image Processing : Image Restoration and Image Segmentation.Image Processing Chapter includes two sections: one calculus of variations methods(energy method), other methods based on PDEs(heat equation and Malik-Perona equation). In studing each of this methods, It has been tried to include experimental results and negative and positive points of them.In Image Segmentation Chapter, first... 

Brain cancer is a lump or tumor in the brain caused by abnormal growth of cells. Glioma is a common type of tumor that develops in the brain. In order to plan precise treatment or accurate tumor removal surgery, brain tumor segmentation is critical for detecting all parts of tumor and its surrounding tissues. To visualize the brain anatomy and detect its abnormalities, we use Magnetic Resonance Imaging (MRI) as an input. Due to many differences in the shape and appearance, accurate segmentation of glioma for identifying all parts of the tumor and its surrounding tissues in cancer detection is a challenging task. Moreover, due to the intensity inhomogeneity existing in brain MRI and gray... 

Correct diagnosis of myocardial scar has always been a major challenge due to the low resolution of cardiac magnetic resonance imaging. The use of a gadolinium-based contrast agent that reveals a scar is the solution proposed in medical science. However, there are limitations to the use of contrast agents in some patients. In recent years, studies based on deep learning techniques have been presented, trying to identify myocardial infarction with the help of images without using contrast agent. This type of diagnosis can be done with the help of different movements of healthy and damaged tissue. Due to the lack of datasets suitable for this application, in this study, real dataset were... 

Computer-Aided Diagnosis (CAD) systems are widely used for detection of various kinds of abnormalities in mammography images. In this work, mass classification is investigated and its steps are explained in detail, for each step a main method is presented and other methods are also discussed. For mass segmentation a relatively new method based on level set and Morphological Component Analysis (MCA) is used.After this step, various kinds of features such as shape, geometrical, and textural ones are introduced. Moreover, a set of proposed features based on wavelet transformation,for this application are presented. The proposed features can describe margin and texture characterizations of a... 

In this thesis, a Segmented Gama Scanning System for measuring total activity of the low/intermediate level radioactive waste drums is designed and a prototype 3-segmented commercial system is manufactured by using NaI detectors. The optimum distance of detector from drum surface and the optimum number of detectors on reconstruction of the radioactivity of the waste drum were studied by MCNP simulations. In addition, the effects of inhomogeneous distribution of radioactivity, the addition of lead filters to detectors, the change in collimator length and the asymmetrical placement of a drum on the rotary plate were also examined by the MCNP calculations. In the absence of a real radioactive... 

Image segmentation has a huge amount of applications in machine vision, target detection, medical image processing, etc. In many medical researches such as Organ and Gland Volume Specification, Analysis of Anatomical Structures and Multimodal Image Registration, Organ
Segmentation is the first step of preprocessing.Since detection of diseases out of medical images depends on organ segmentation results,the segmentation process is done by experts which has a lot of disadvantages such as high time computation, high cost, etc. Hence, designing algorithms that can segment images with high accuracy and need minimum user interaction are desirable. So, in this thesis, a new
knowledge based... 

Dynamic hand gesture is an efficient approach used in Human Computer Interaction (HCI). The goal is to recognize and analyze the different hand gestures in a recorded video. There are some associated challenges such as video noises, illumination changes, rotation variance, hand occlusion which make the process more complicated.To do the research we used five different gestures out of the Sheffield hand gesture dataset which is collected from six persons under three different backgrounds and two illumination conditions. This procedure needs image processing in order to detect and segment the important parts involved in images such as hands and analyzing the changes and motions of them. We... 

Image segmentation is a technique which divides an image into significant parts. The accuracy of this technique plays an important role when it applies on medical images. Among various image segmentation methods, clustering methods have been extensively investigated and used. Since it is an unsupervised method, the existence of a small amount of side-information which is extracted from a specific application (in this case, medical image) could improve its accuracy. Using this side-information in clustering methods introduces a new generation of clustering approaches called semi-supervised clustering. This information usually has a format of pair-wise constraints and can be prepared easily... 

One of the most applicable fields in data mining is customer relationship management (CRM). CRM process includes four aspects: Customer identification, Customer attraction, Customer retention, and Customer development. Data mining can be a supportive tool for decision making in each of these CRM aspects. Huge volume of data and information corresponding to CRM that exists in companies' databases, has made sufficient potential for data mining process and discovering hidden knowledge. Importance of concepts like customer needs identification, customer retention, and increasing customer value for companies has made the need to use of data mining techniques more valuable. Saipa Yadak Co., as a... 

Laparoscopic surgery is a branch of minimally invasive surgery that is implemented in the abdominal cavity. This kind of surgery is conducted using surgical instruments that are inserted into the abdomen through some small incisions created on its wall and the necessary vision is provided for the surgeon using a laparoscope lens that is inserted through the first created incision. In recent years, because of its advantages, controlling and manipulation of the lens is done using some robots instead of surgeon assistant. To facilitate the controlling procedure of these robots for the surgeon, several controlling modes such as keyboard, foot switch, and voice commands are presented. Robolens is... 

In this study a variational framework for joint segmentation and motion estimation is provided for inspecting heart in Cine MRI sequences. In the first work, a functional including Mumford-Shah segmentation and optical flow based dense motion estimation is proposed. However, the motion estimation technique is replaced with warping estimation in the second work to reach in more regular and smooth motion field based on tracking of cardiac boundaries. Both of these functionals are then approximated by using the phase-field method to make them suitable for extracting Euler-Lagrange equations. Numerical solution to the optimization problem, when the time and image spaces are discretized by finite... 

Banks and financial services typically focus on geographic, demographic, socio-economic, and psychological characteristics to segment the market, in spite of the fact that these are not efficient predictors of future buying behavior of customers. In the present study, benefit segmentation has been used to group retail banking customers in relation to their particular attitudes and behavior. In particular, the identification and measurement of the two major dimensions of service quality, process (how the service is delivered) and outcome (what is delivered) have been investigated to better understand of what constitutes service quality from the customer’s viewpoint. In order to derive... 

Digital watermarking is an efficacious technique to protect the copyright and ownership of digital information. Traditional image watermarking algorithms embed a logo in the image that could reduce its visual quality. A new approach in watermarking called zero watermarking doesn’t need to embed a logo in the image. In this algorithm we find a feature from the main image and combine it with a logo to obtain a key. This key is securely kept by a trusted authority. In this thesis we show that we can increase the robustness of digital zero watermarking by a new counter detection method in comparison to Canny Edge detection and morphological dilatation that is mostly used by related works....