Sharif Digital Repository

Today, due to the increasing activity of terrorist groups, monitoring people in important and busy places such as airports and train stations is very important. One of the technologies that has been developed for this purpose in recent years is 3D imaging technology using millimeter wave. These systems use millimeter waves to image people and identify objects hidden under clothing, which do not have the limitations of conventional imaging techniques such as x-rays and metal detectors. One of the advantages of using these systems is the ability to automatically detect objects in millimeter wave images using deep neural networks such as Segmented, Faster R-CNN and Mask R-CNN, which using these... 

Histopathology images are a type of medical images that are used to diagnose a variety of diseases. One of these illnesses is the Leukemia cancer, which has four different subtypes and is diagnosed using a blood smear image. As a result of the advancement of deep learning tools, models for diagnosing various types of disease from images have been developed in recent years.In this project, one of the best models developed to diagnose four different types of disease was replicated, and it was demonstrated that, while this model achieves acceptable accuracy, its decision is not based on medically significant criteria. In the following, a general method for diagnosing the disease is proposed... 

This research mainly aims to propose, for the first time, a way of generating text from Abstract Meaning Representation (AMR) in Persian. AMR is a rather new way of representing the meaning of natural language sentences, that captures the various semantic components in a rooted, directed, acyclic graph. Generating text from AMR is a challenging task in natural language processing as some syntactic constructs are abstracted away from the representation, resulting in one single AMR having multiple translations. Considering many applications of generating text from meaning representations in natural language processing it seems inevitable to design some methods for converting such... 

Parkinson’s disease is considered as a progressive neurodegenerative disease that hasn’t any certain treatment. In Iran until 1390, there were about 150 thousand patient struggling with this disease. Rehabilitation is known as an effective treatment to decrease destructive progress of the disease. Because of motional problems of PD patients, it is hard to come to the clinics. So developing remote rehabilitation would be interested by researchers and occupational therapists. Therefore in the recent years, an activity recognition system has been developed in Mowafaghian research center. This system is based on IMU sensors and a NM classifier.These systems are challenging with some problems,... 

In this thesis, we introduced a new augmentation method that takes into account the inherent properties of trajectory data and regenerates valid trajectories while preserving all the distinctive features of the main path. Our method uses Dynamic movement primitives (DMP) formulation, which is widely used in path generation in robotics, to manipulate the data in a kinematically accurate way. We implemented the presented method on our Iranian sign language data set by augmenting each group in our data set with a proper form of our DMP data augmentation method. After training our augmented data set with two deep classification models, We achieved 82.95 percent maximum and 77.61 percent mean... 

Large data sources labeled by experts at cost are essential for deep learning success in various domains. But, when labeling is expensive and labeled data is scarce, deep learning generally does not perform well. The goal of semi-supervised learning is to leverage abundant unlabeled data that one can easily collect. New semi-supervised algorithms based on data augmentation techniques have reached new advances in this field. In this work, by studying different textual augmentation techniques, a new approach is proposed that can obtain effective information signals from unlabeled data. The method encourages the model to generate the same representation vectors for different augmented versions... 

Researchers working at Mowafaghian Rehabilitation Research Center have decided to develop a telerehabilitation system named SEPANTA, especially designed for activity recognition of Parkinson's Disease patients. In this regard, the system uses 34 mobility exercises, including 20 LSVT-BIG activities (especially designed for PD patients) and 14 functional daily activities. Human Activity Recognition (HAR) systems faces various challenges e.g., intra-class variabilities, meaning differences in an activity performance by different persons or a person. Data augmentation and utilizing deep learning models are the most common solutions for the risen challenges. However, deep structures require an... 

Action recognition has a lot of applications in everyday human life. In the past, the researchers concentrated on using RGB frames, but since the advent of 3-dimensional sensors such as Kinect, 3D action recognition drew researchers' attention. Kinect can extract the joints of the body in action as time series. One of the main challenges of action recognition is that different individuals perform an action with various styles and speeds. Hence, the conventional methods such as calculating Euclidean distance seem inappropriate for this task. One solution is to use the techniques such as DTW, which aims to temporal aligning of the sequences. The DTW is not a metric distance; hence, in this... 

Many workers and soldiers suffer from musculoskeletal problems due to carrying heavy loads. Using exoskeleton robots which are designed for power augmentation can be effective in preventing these disorders. Due to the interaction of these robots with human, it is necessary to design an appropriate control system for these robots, therefore, the aim of this research is to design a predictive nonlinear control system for a three degrees of freedom lower-limb Exoskeleton robot, in order to improve the performance of the robot, follow trajectory of human joints and reduce the interaction forces between human and the robot during the squatting activity. Multi-stage model predictive controller...