An Engineering Evaluation on the Glimpse of Satellite Image Pre-processing Utility Tools

The advancement of technology in the area of satellite remote sensing has been generating voluminous amount of satellite images at regular intervals regularly. The satellite image analysis derive very useful, invaluable and essential inputs for various applications such as disaster management, civil aviation, meteorology, ocean observation systems, earth science studies and defense applications, etc. The satellite image analysis technique provides the necessary inputs for image preprocessing systems as a basic prerequisite and essential ingredient. Over the past several years many satellite image preprocessing tools have been developed with various features. The choice of satellite image preprocessing tools basically depend on the purpose of image analysis, the features of satellite image preprocessing tools and the specific need and application. Due to a large number of applications of satellite images, user has a wide ranging choice to select optimally the right preprocessing tool for the right application. Thus, the present study helps in aiding the proper understanding and selection of the various satellite image preprocessing tools and their features for any specific application. To facilitate this scheme, the current study has identified various satellite image preprocessing tools and prominent features of the desired tool. Briefly, the study presents a clear understanding with specific examples on the various available tools and features for the user specific application for the desired satellite images. The various features of the satellite image preprocessing tools have been presented in detail for ready reference, guidance and usage

Analyzing and Improving Generative Adversarial Training for Generative Modeling and Out-of-Distribution Detection

Generative adversarial training (GAT) is a recently introduced adversarial defense method. Previous works have focused on empirical evaluations of its application to training robust predictive models. In this paper we focus on theoretical understanding of the GAT method and extending its application to generative modeling and out-of-distribution detection. We analyze the optimal solutions of the maximin formulation employed by the GAT objective, and make a comparative analysis of the minimax formulation employed by GANs. We use theoretical analysis and 2D simulations to understand the convergence property of the training algorithm. Based on these results, we develop an incremental generative training algorithm, and conduct comprehensive evaluations of the algorithm's application to image generation and adversarial out-of-distribution detection. Our results suggest that generative adversarial training is a promising new direction for the above applications

Shifting perspectives: holography and the emergence of technical communities

Holography, the technology of three-dimensional imaging, has repeatedly been reconceptualised by new communities. Conceived in 1947 as a means of improving electron microscopy, holography was revitalized in the early 1960s by engineer-scientists at classified laboratories. The invention promoted the transformation of a would-be discipline (optical engineering) and spawned limited artist-scientist collaborations. However, a separate artisanal community promoted a distinct countercultural form of holography via a revolutionary technology: the sandbox optical table. Their tools, sponsorship, products, literature and engagement with wider culture differentiated the communities, which instituted a limited ‘technological trade’. The subject strikingly illustrates the co-evolution of new technology along with highly dissimilar user groups, neither of which fostered the secure establishment of a profession or discipline. The case generalises the concept of 'research-technologists' and 'peripheral science', and extends the ideas of Langdon Winner by demonstrating how the political dimensions of a technology can be important but evanescent in the growth of technical communities