Problem-specific robotic algorithms and generic machine learning approaches to robotics have complementary strengths and weaknesses, trading-off data-efficiency and generality. To find the right balance between these, we propose to use robotics-specific information encoded in robotic algorithms together with the ability to learn task-specific information from data. We demonstrate this approach ...

Aluminium/alumina/graphite hybrid metal matrix composites manufactured using stir casting technique was subjected to machining studies to predict tool condition during machining. Fresh tool as well as tools with specific amount of wear deliberately created prior to machining experiments was used. Vibration signals were acquired using an accelerometer for each tool condition. These signals were ...

Image registration is the most important fundamental phenomenon in the image processing system. In which Automatic image registration is a challenging aspect. Although enormous methods for automatic image registration have been developed and implemented in ancient days, it is still a broad use in plenty applications, such as in remote sensing. In my work, I have proposed a method for automatic ...

In this work, a new event detection method for power quality analysis based on the statistical analysis of adaptive decomposition signals is presented. The combination of an adaptive prediction filter-based subband decomposition structure with a rule-based histogram analysis block produced successful detection and classification parameters on our real life power system transient data. Proposed ...

This paper presents a novel scene change detection method using complexity and edge direction based on intra prediction mode in H.264/AVC compressed video. When scene change occurs, there is less temporal correlation between consecutive frames. Therefore, most of macro-blocks are encoded in intra mode. Using this property, the proposed method calculates the percentage of intra mode blocks in ea...

Problem-specific algorithms and generic machine learning approaches have complementary strengths and weaknesses, trading-off data efficiency and generality. To find the right balance between these, we propose to use problem-specific information encoded in algorithms together with the ability to learn details about the problem-instance from data. We demonstrate this approach in the context of st...

The data presented here were originally collected for the research project "CT-Scan processing and analysis in patient with breast cancer after radiotherapy". Also, it reported in our study "Prediction of Lung Tissue Damage by Evaluating Clinical and Dosimetric Parameters in Breast Cancer Patients" (Hasanabdali et al., 2016) [1]. This article describes and directly links to 52 subjects referred...

Many works have demonstrated that the performance of the prediction error (PE) based reversible watermarking algorithm depends on the precision of the prediction value. However, most algorithms compute the prediction value by exploiting only the correlation between the embedding pixel and its neighboring pixels, thus limiting the watermarking performance of these algorithms. In this work, we ob...

Page | 60 Capacity Enhancement of Reversible Data Hiding Technique Using Adaptive Embedding Cheenu Bansal, Preeti Gupta ABSTRACT: Reversible data hiding is current research area in field of data hiding. Reversible data hiding is defined as the process of hiding secret data in such a way that at receiver side both secret message and cover image can be recovered. This kind of reversibility is req...