DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs

We present a novel deep learning architecture for fusing static multi-exposure images. Current multi-exposure fusion (MEF) approaches use hand-crafted features to fuse input sequence. However, the weak hand-crafted representations are not robust to varying input conditions. Moreover, they perform poorly for extreme exposure image pairs. Thus, it is highly desirable to have a method that is robust to varying input conditions and capable of handling extreme exposure without artifacts. Deep representations have known to be robust to input conditions and have shown phenomenal performance in a supervised setting. However, the stumbling block in using deep learning for MEF was the lack of sufficient training data and an oracle to provide the ground-truth for supervision. To address the above issues, we have gathered a large dataset of multi-exposure image stacks for training and to circumvent the need for ground truth images, we propose an unsupervised deep learning framework for MEF utilizing a no-reference quality metric as loss function. The proposed approach uses a novel CNN architecture trained to learn the fusion operation without reference ground truth image. The model fuses a set of common low level features extracted from each image to generate artifact-free perceptually pleasing results. We perform extensive quantitative and qualitative evaluation and show that the proposed technique outperforms existing state-of-the-art approaches for a variety of natural images.Comment: ICCV 201

Numerical Simulations of Flow in a 3-D Supersonic Intake at High Mach Numbers

Numerical simulations of the compressible, 3-D non reacting flow in the engine inlet sectionof a concept hypersonic air-breathing vehicle are presented. These simulations have been carriedout using FLUENT. For all the results reported, the mesh has been refined to achieve areaaveragedwall y+ about 105. Mass flow rate through the intake and stagnation pressure recoveryare used to compare the performance at various angles of attack. The calculations are able topredict the mode of air-intake operation (critical and subcritical) for different angles of attack.Flow distortion at the intake for various angles of attack is also calculated and discussed. Thenumerical results are validated by simulating the flow through a 2-D mixed compression hypersonicintake model and comparing with the experimental data

Recent direct measurement of the Top quark mass and quasi-infrared fixed point

We note that the recent direct measurement of the top quark mass at $173.3 \pm 5.6 (stat) \pm 6.2 (syst)$ by D0 collaboration severely constrains the theoretically attractive infra-red fixed point scenario of the top quark Yukawa coupling in supersymmetric GUTs. For one-step unified models the above mentioned measurement bounds the arbitrary but experimentally determinable parameter $\tan \beta$ to the range $1.3 \le \tan \beta \le 2.1$. Further crunch on the top quark mass may determine $\tan \beta$ even more accurately within the fixed point scenario. On the other hand an experimental value of $\tan \beta > 2.1$ will rule out the fixed point scenario bounding $h^2_t(M_X)/4 \pi$ to 0.022 from above.Comment: 7 pages, Latex with epsf style, 1 figure, captions.st

Common fixed point theorems of different compatible type mappings using Ciric\u27s contraction type condition

The purpose of this paper is to establish necessary and sufficient conditions for the existence of common fixed points for a compatible pair of selfmaps under Ciric\u27s contraction type condition. These theorems improve and generalize the results of Mukherjee and Verma [11] and Jungck [9] to a pair of selfmaps. Also established the existence of common fixed points for a pair of compatible mappings of type (B), and obtain a result on the existence of common fixed points for a pair of compatible mappings of type (A) as corollary. Greguš fixed point theorem follows as a special case to our results

Modeling charge transport in Swept Charge Devices for X-ray spectroscopy

We present the formulation of an analytical model which simulates charge transport in Swept Charge Devices (SCDs) to understand the nature of the spectral redistribution function (SRF). We attempt to construct the energy-dependent and position dependent SRF by modeling the photon interaction, charge cloud generation and various loss mechanisms viz., recombination, partial charge collection and split events. The model will help in optimizing event selection, maximize event recovery and improve spectral modeling for Chandrayaan-2 (slated for launch in 2014). A proto-type physical model is developed and the algorithm along with its results are discussed in this paper.Comment: 9 pages, 7 figures, Proc. SPIE 8453, High Energy, Optical, and Infrared Detectors for Astronomy