Sharif Digital Repository

Detection degradation caused by distribution discrepancy between the training and testing domains is a common problem in object detection systems. The difference between training and testing domains’ distribution mainly happenes because of the different ways of collecting and gathering data. For instance, datasets which have images with different illumination, view point, resolution, background and are obtained by different acquisition systems, have variance in distribution. The solution toward improving the detection rate of the classifier trained on training (source) domain when it is applied on testing (target) domain is to use Domain Adaptation (DA) techniques. One of important branches... 

Transformer are one of the most important equipment in transmission and distribution network. Transformer unplanned outage have severe impacts on the continuity of power system operation and is also an irreparable economic harm to power network operators. To improve the reliability of transformers and to achieve an optimum operation cost, online condition monitoring is inevitbale. Information about the quality of the transformer insulation system is known as the best parameter to be monitored in transformer. Since partiale discharge (PD) signals are initiated long before the beginning of a severe damage, monitoring and its evaluation can be employed to warn the operator. Data mining on the... 

Target recognition techniques based on micro Doppler phenomenon are popular because they are applicable even on low resolution radars, in contrast to other techniques such as High Resolution Range Profile (HRRP) which need high resolution in range or angle. Usually, main purpose of such techniques is generating robust features against target initial state, velocity, aspect angle, etc. rather than features which exactly identify a target. Main approaches in the literature are based on time-frequency transforms (TFT) such as spectrogram in order to generate features to classify targets, but in this thesis, we propose a totally different method using Recurrence Plot for generating features... 

Digital video is one of the biggest part of digital data. The first step of digital video analytics is shot boundary detection. We used overlapped partitioning beside color histogram in uncompressed data and macroblock type prediction in compressed data as feature and supervised classifiers for decision making. Tests on TRECVID 2006 shows 8.9% improvement of F-measure in uncompressed video and 5.3% in h.264 bitstream. Supplementary test is done on IRIB dataset which shows 5.7% improvement of F-measure in uncompressed and 3.2% in H.264. H.264 based algorithm is almost 7 times faster in comparison to the algorithm that includes decoding  

Transformers are the key component in power system transmission and distribution networks. Condition based maintenance will increase their expected life and online monitoring is essential to ensure operation reliability. In this work a new approach to transformer online monitoring is provided based on partial discharge (PD) measurement.Multi-source PD signal separated using time-frequency S transform (ST) that is applied to the PD signal waveforms. The resultant ST matrix is then converted to gray scale image from which high level features are extracted using Bag of Words (BoW). Gaussian mixture model (GMM) clustering is used to discover clusters in the feature space. For recognition of...