Object Level Deep Feature Pooling for Compact Image Representation

Convolutional Neural Network (CNN) features have been successfully employed in recent works as an image descriptor for various vision tasks. But the inability of the deep CNN features to exhibit invariance to geometric transformations and object compositions poses a great challenge for image search. In this work, we demonstrate the effectiveness of the objectness prior over the deep CNN features of image regions for obtaining an invariant image representation. The proposed approach represents the image as a vector of pooled CNN features describing the underlying objects. This representation provides robustness to spatial layout of the objects in the scene and achieves invariance to general geometric transformations, such as translation, rotation and scaling. The proposed approach also leads to a compact representation of the scene, making each image occupy a smaller memory footprint. Experiments show that the proposed representation achieves state of the art retrieval results on a set of challenging benchmark image datasets, while maintaining a compact representation.Comment: Deep Vision 201

NAG: Network for Adversary Generation

Adversarial perturbations can pose a serious threat for deploying machine learning systems. Recent works have shown existence of image-agnostic perturbations that can fool classifiers over most natural images. Existing methods present optimization approaches that solve for a fooling objective with an imperceptibility constraint to craft the perturbations. However, for a given classifier, they generate one perturbation at a time, which is a single instance from the manifold of adversarial perturbations. Also, in order to build robust models, it is essential to explore the manifold of adversarial perturbations. In this paper, we propose for the first time, a generative approach to model the distribution of adversarial perturbations. The architecture of the proposed model is inspired from that of GANs and is trained using fooling and diversity objectives. Our trained generator network attempts to capture the distribution of adversarial perturbations for a given classifier and readily generates a wide variety of such perturbations. Our experimental evaluation demonstrates that perturbations crafted by our model (i) achieve state-of-the-art fooling rates, (ii) exhibit wide variety and (iii) deliver excellent cross model generalizability. Our work can be deemed as an important step in the process of inferring about the complex manifolds of adversarial perturbations.Comment: CVPR 201

ISOLATION, CHARACTERIZATION AND VALIDATION OF HPLC METHOD FOR QUANTIFICATION OF BIS-[10-(2-METHYL-4H-3-THIA-4,9-DIAZABENZO[F]AZULENE)]-1,4-PIPERAZINE IN AN ANTI-PSYCHOTIC DRUG SUBSTANCE, OLANZAPINE

Objective: The main objective of present study was to Isolate, characterize and validate a reverse phase high performance liquid chromatographic method was validated for quantification of bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine in Olanzapine drug substance; it decreases the mental disorders in human body. The method is specific, rapid, precise and accurate for the separation and determination of bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine in Olanzapine drug substance form.Methods: The bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine of Olanzapine was resolved on a Zorbax RX-C 8, 250 mm X 4.6 mm, 5 micron column (L-1) using a mobile phase system containing 0.03 M sodium dodecyl sulphate in water pH 2.5 with 1 N sodium hydroxide solution and acetonitrile in the ratio of (Mobile phase A-52:48 v/v) and (Mobile phase B-buffer and Acetonitrile 30:70 v/v) by using the gradient program. The mobile phase was set at a flow rate of 1.5 ml/min and the volume injected was 20μl for every injection. The detection wavelength was set at 220 nm and the column temperature was set at 35 °C.Results: The proposed method was productively applied for the quantitative determination of bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo [f]azulene)]-1,4-piperazine in Olanzapine drug substance form. The linear regression analysis data for calibration plots showed a good linear relationship over a concentration range of 0.025to 0.903 µg/ml for bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine, 0.081-0.608 µg/ml for Olanzapine. The mean values of the correlation coefficient were 0.999 and 0.999 for bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine and Olanzapine. The method was validated as per the ICH guidelines. The detection limit (LOD) was about 0.007 µg/ml, 0.024 µg/ml and quantitation limit (LOQ) was about 0.024 µg/ml, 0.081 µg/ml for bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine and Olanzapine. The relative standard deviation was found to be 1.64 % and 2.18 % for bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine and Olanzapine.Conclusion: The validated HPLC method and the statistical analysis showed that the method is repeatable and selective for the estimation of the bis-[10-(2-methyl-4H-3-thia-4,9-diazabenzo[f]azulene)]-1,4-piperazine of the Olanzapine drug substance

Effect Of Ph On The Physical Properties Of Znin2se4 Thin Films Grown By Chemical Bath Deposition

Recently there has been much interest on the preparation and characterization of ternary semiconducting materials, mainly ZnIn2Se4 (ZIS) due to its potential applications in various fields, particularly as a buffer layer in the fabrication of heterojuction solar cells. In the present work, thin films of ZIS have been synthesized by a simple and economic method, chemical bath deposition at different pH values that vary from 9 to 11. The deposition was carried out for a fixed bath temperature (Tb) of 90 °C and constant reaction time of 60 min. Ammonia and hydrazine hydrate were used as complexing agents. The chemical and physical properties of the deposited ZIS films were analyzed using appropriate techniques. The X-ray diffraction analysis revealed that the deposited films were polycrystalline and showed (112) peak as the preferred orientation. Scanning electron micrographs revealed that the samples had large number of granule like particles in different sizes. The optical transmittance of these samples was found to be > 75 % in the visible region and the evaluated energy band gap varied from 2.15 eV to 2.64 eV with the change of pH value in the range, 9 - 11. The detailed study of these results were presented and discussed. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/939

Improved RISC Processor Design Using MIPS Instruction Set Approach

Processor's are playing vital role in today's environment. A lot many processor's are into the market but daily a new processor is making its position in the society. The trade off parameter's of VLSI are playing a key role in the selecting the particular processor for its application. In the days a Low Power and Low Area circuit is to be designed. This paper totally concentrates on synthesizing a low power processor in Verilog HDL. The complexity of the processor can be increased by making it suitable for low power applications. DOI: 10.17762/ijritcc2321-8169.15052