Visual Monocular Obstacle Avoidance for Small Unmanned Vehicles

This paper presents and extensively evaluates a visual obstacle avoidance method using frames of a single camera, intended for application on small devices (ground or aerial robots or even smartphones). It is based on image region classification using so called relative focus maps, it does not require a priori training, and it is applicable in both indoor and outdoor environments, which we demonstrate through evaluations using both simulated and real data

Feature-Based Target Detection and Classification in Passive ISAR Range-Crossrange Images

We present a method for passive ISAR image analysis for target detection, feature extraction and shape-based classification without a priori target shape information. Results show that classification is possible with limited target samples

Flying Target Detection and Recognition by Feature Fusion

This paper presents a near-realtime visual detection and recognition approach for flying target detection and recognition. Detection is based on fast and robust background modeling and shape extraction, while recognition of target classes is based on shape and texture fused querying on a-priori built real datasets. Main application areas are passive defense and surveillance scenarios

Forecasting change based on employees' work engagement: case study (civil servants in government organizations in Sanandaj)

The study tries to identify predictors of change acceptance based on work engagement of civil servants in government organizations in Sanandaj. The population of the study is 4235 civil servants in government organizations in Sanandaj. The present study uses stratified random sampling method. Using Cochran's Formula, as many as 352 people were set as the sample size and the same number of questionnaires was filled by the participants. The study was descriptive co relational and was carried out through a descriptive method. A questionnaire was used for data collection to measure the level of work engagement, the questionnaire proposed by Schaufeli and Becker (2003) was used. To measure change acceptance in the respondents, the questionnaire proposed by Saeatchi, Kamkari and Askarian (2010) was designed according to the model by Kurt Lewin. After the validity and reliability of the questionnaires were confirmed, the questionnaires were distributed among the participants. Cronbach's alpha in work engagement and in change acceptance questionnaires were 0.84 and 0.82, respectively. After completing the questionnaire using SPSS20, Pearson correlation analysis and multivariate regression analysis were calculated and analyzed. The results of regression analysis showed that the dependent variable (change acceptance) was directly affected by liveliness and eagerness of the staff. This variable alone explains 44% of acceptance of change variance in this study. The independent variable is directly affected by eagerness variable. This variable alone accounts for 39% of accepting change variance in the population under study. The third determinant of accepting change is the employees' dedication variable. This variable alone amounts to 31% of change acceptance variance by staff in the population under study

Focus area extraction by blind deconvolution for defining regions of interest

We present an automatic focus area estimation method, working with a single image without a priori information about the image, the camera or the scene. It produces relative focus maps by localized blind deconvolution and a new residual error based classification. Evaluation and comparison is performed, and applicability is shown through image indexing