Spectral-spatial classification of hyperspectral images: three tricks and a new supervised learning setting

Spectral-spatial classification of hyperspectral images has been the subject of many studies in recent years. In the presence of only very few labeled pixels, this task becomes challenging. In this paper we address the following two research questions: 1) Can a simple neural network with just a single hidden layer achieve state of the art performance in the presence of few labeled pixels? 2) How is the performance of hyperspectral image classification methods affected when using disjoint train and test sets? We give a positive answer to the first question by using three tricks within a very basic shallow Convolutional Neural Network (CNN) architecture: a tailored loss function, and smooth- and label-based data augmentation. The tailored loss function enforces that neighborhood wavelengths have similar contributions to the features generated during training. A new label-based technique here proposed favors selection of pixels in smaller classes, which is beneficial in the presence of very few labeled pixels and skewed class distributions. To address the second question, we introduce a new sampling procedure to generate disjoint train and test set. Then the train set is used to obtain the CNN model, which is then applied to pixels in the test set to estimate their labels. We assess the efficacy of the simple neural network method on five publicly available hyperspectral images. On these images our method significantly outperforms considered baselines. Notably, with just 1% of labeled pixels per class, on these datasets our method achieves an accuracy that goes from 86.42% (challenging dataset) to 99.52% (easy dataset). Furthermore we show that the simple neural network method improves over other baselines in the new challenging supervised setting. Our analysis substantiates the highly beneficial effect of using the entire image (so train and test data) for constructing a model.Comment: Remote Sensing 201

Descreening of Color Halftone Images in the Frequency Domain

Scanning a halftone image introduces halftone artifacts, known as Moiré patterns, which significantly degrade the image quality. Printers that use amplitude modulation (AM) screening for halftone printing position dots in a periodic pattern. Therefore, frequencies relating halftoning are easily identifiable in the frequency domain. This paper proposes a method for descreening scanned color halftone images using a custom band reject filter designed to isolate and remove only the frequencies related to halftoning while leaving image edges sharp without image segmentation or edge detection. To enable hardware acceleration, the image is processed in small overlapped windows. The windows are filtered individually in the frequency domain, then pieced back together in a method that does not show blocking artifacts

Barriers to the adoption of renewable and energy-efficient technologies in the Vietnamese power sector

This paper examines the major barriers to the deployment of geothermal, small hydro and advanced coal power generation technologies in Vietnam. It ranks their severity by applying the analytical hierarchy process to data from a survey of 37 domestic experts and stakeholders. Key barriers to a wider penetration of small hydro generation technologies are insufficient capital, a lack of domestic suppliers and unsatisfactory government policies. Barriers to geothermal power are related to information and awareness problems, a lack of R&D and industrial capability, a weak policy framework and the remoteness of geothermal sites. For advanced coal power technologies, the barriers are weak industrial capability, high cost and a lack of technical knowledge. The experts consulted in this study view changes in government actions as the key to overcoming the abovementioned barriers. They recommend investing more in R&D activities, improving R&D capacity through joint-venture schemes and reforming investment policy/legislation for the electric power industry as the most appropriate solutions.analytical hierarchy process; renewables; energy efficient technologies.

Fostering Cooperation in Structured Populations Through Local and Global Interference Strategies

We study the situation of an exogenous decision-maker aiming to encourage a population of autonomous, self-regarding agents to follow a desired behaviour at a minimal cost. The primary goal is therefore to reach an efficient trade-off between pushing the agents to achieve the desired configuration while minimising the total investment. To this end, we test several interference paradigms resorting to simulations of agents facing a cooperative dilemma in a spatial arrangement. We systematically analyse and compare interference strategies rewarding local or global behavioural patterns. Our results show that taking into account the neighbourhood's local properties, such as its level of cooperativeness, can lead to a significant improvement regarding cost efficiency while guaranteeing high levels of cooperation. As such, we argue that local interference strategies are more efficient than global ones in fostering cooperation in a population of autonomous agents.</p

Structure Functions of Nuclei at Small x and Diffraction at HERA

Gribov theory is applied to investigate the shadowing effects in the structure functions of nuclei. In this approach these effects are related to the process of diffractive dissociation of a virtual photon. A model for this diffractive process, which describes well the HERA data, is used to calculate the shadowing in nuclear structure functions. A reasonable description of the x, Q^2 and A-dependence of nuclear shadowing is achieved.Comment: TeX, 10 pages, 7 figures in 6 ps-file

Hard Diffraction at HERA and the Gluonic Content of the Pomeron

We show that the previously introduced CKMT model, based on conventional Regge theory, gives a good description of the HERA data on the structure function F_2^D for large rapidity gap (diffractive) events. These data allow, not only to determine the valence and sea quark content of the Pomeron, but also, through their Q^2 dependence, give information on its gluonic content. Using DGLAP evolution, we find that the gluon distribution in the Pomeron is very hard and the gluons carry more momentum than the quarks. This indicates that the Pomeron, unlike ordinary hadrons, is a mostly gluonic object. With our definition of the Pomeron flux factor the total momentum carried by quarks and gluons turns out to be 0.3-0.4 - strongly violating the momentum sum rule.Comment: C-Shell archive of a PostScript file containing a 20 page paper with text and 12 figures in i

Strange Baryon Production in Heavy Ion Collisions

The rapidity distribution of $\Lambda$ and $\bar{\Lambda}$ produced in nucleus-nucleus collisions at CERN energies is studied in the framework of an independent string model - with quark-antiquark as well as diquark-antidiquark pairs in the nucleon sea. It is shown that, besides the $\Lambda$-$\bar{\Lambda}$ pair production resulting from the fragmentation of sea diquarks, final state interactions of co-moving secondaries $\pi + N \to K + \Lambda$ and $\pi + \bar{N} \to K + \bar{\Lambda}$ are needed in order to reproduce the data. Predictions for $Pb$-$Pb$ collisions are presented.Comment: Plain TeX + epsf, 40 pages; 1 Postscript-table and 7 Postscript figures (uuencoded

SnO2 based glasses : A viable photonic system

The present work focuses on sol-gel derived SnO2-based thin glass-ceramic films doped with Er3+ ions, fabricated by dipcoating technique. Our goal is to find a viable fabrication protocol to obtain them. Thin films with a variety of composition were synthesized and their structural, optical and spectroscopic properties were investigated. The FTIR spectra and X-ray diffraction patterns were used to characterize the structure of the thin films. The transparency of the thin film was tested by UV-Vis transmittance measurements. The energy transfer dynamic was investigated by time-resolved spectroscopy and photoluminescence measurements