Exploiting context information to aid landmark detection in SenseCam images

In this paper, we describe an approach designed to exploit context information in order to aid the detection of landmark images from a large collection of photographs. The photographs were generated using Microsoft’s SenseCam, a device designed to passively record a visual diary and cover a typical day of the user wearing the camera. The proliferation of digital photos along with the associated problems of managing and organising these collections provide the background motivation for this work. We believe more ubiquitious cameras, such as SenseCam, will become the norm in the future and the management of the volume of data generated by such devices is a key issue. The goal of the work reported here is to use context information to assist in the detection of landmark images or sequences of images from the thousands of photos taken daily by SenseCam. We will achieve this by analysing the images using low-level MPEG-7 features along with metadata provided by SenseCam, followed by simple clustering to identify the landmark images

Finding What You Need, and Knowing What You Can Find: Digital Tools for Palaeographers in Musicology and Beyond

This chapter examines three projects that provide musicologists with a range of resources for managing and exploring their materials: DIAMM (Digital Image Archive of Medieval Music), CMME (Computerized Mensural Music Editing) and the software Gamera. Since 1998, DIAMM has been enhancing research of scholars worldwide by providing them with the best possible quality of digital images. In some cases these images are now the only access that scholars are permitted, since the original documents are lost or considered too fragile for further handling. For many sources, however, simply creating a very high-resolution image is not enough: sources are often damaged by age, misuse (usually Medieval ‘vandalism’), or poor conservation. To deal with damaged materials the project has developed methods of digital restoration using mainstream commercial software, which has revealed lost data in a wide variety of sources. The project also uses light sources ranging from ultraviolet to infrared in order to obtain better readings of erasures or material lost by heat or water damage. The ethics of digital restoration are discussed, as well as the concerns of the document holders. CMME and a database of musical sources and editions, provides scholars with a tool for making fluid editions and diplomatic transcriptions: without the need for a single fixed visual form on a printed page, a computerized edition system can utilize one editor’s transcription to create any number of visual forms and variant versions. Gamera, a toolkit for building document image recognition systems created by Ichiro Fujinaga is a broad recognition engine that grew out of music recognition, which can be adapted and developed to perform a number of tasks on both music and non-musical materials. Its application to several projects is discussed

Testing Convolutional Neural Networks for finding strong gravitational lenses in KiDS

Convolutional Neural Networks (ConvNets) are one of the most promising methods for identifying strong gravitational lens candidates in survey data. We present two ConvNet lens-finders which we have trained with a dataset composed of real galaxies from the Kilo Degree Survey (KiDS) and simulated lensed sources. One ConvNet is trained with single \textit{r}-band galaxy images, hence basing the classification mostly on the morphology. While the other ConvNet is trained on \textit{g-r-i} composite images, relying mostly on colours and morphology. We have tested the ConvNet lens-finders on a sample of 21789 Luminous Red Galaxies (LRGs) selected from KiDS and we have analyzed and compared the results with our previous ConvNet lens-finder on the same sample. The new lens-finders achieve a higher accuracy and completeness in identifying gravitational lens candidates, especially the single-band ConvNet. Our analysis indicates that this is mainly due to improved simulations of the lensed sources. In particular, the single-band ConvNet can select a sample of lens candidates with $\sim40\%$ purity, retrieving 3 out of 4 of the confirmed gravitational lenses in the LRG sample. With this particular setup and limited human intervention, it will be possible to retrieve, in future surveys such as Euclid, a sample of lenses exceeding in size the total number of currently known gravitational lenses.Comment: 16 pages, 10 figures. Accepted for publication in MNRA

Texture based Image Splicing Forgery Recognition using a Passive Approach

With the growing usage of the internet in daily life along with the usage of dominant picture editing software tools in creating forged pictures effortlessly, make us lose trust in the authenticity of the images. For more than a decade, extensive research is going on in the Image forensic area that aims at restoring trustworthiness in images by bringing various tampering detection techniques. In the proposed method, identification of image splicing technique is introduced which depends on the picture texture analysis which characterizes the picture areas by the content of the texture. In this method, an image is characterized by the regions of their texture content. The experimental outcomes describe that the proposed method is effective to identify spliced picture forgery with an accuracy of 79.5%

HEP-2 CELL IMAGES FLUORESCENCE INTENSITY CLASSIFICATION TO DETERMINE POSITIVITY BASED ON NEURAL NETWORK AMIN

Nowadays, the recommended method for detection of anti-nuclear auto-antibodies is by using Indirect Immunofluorescence (IIF). The increasing of test demands on classification of Hep-2 cell images force the physicians to carry out the test faster, resulting bad quality results. IIF diagnosis requires estimating the fluorescence intensity of the serum and this will be observed. As there are subjective and inter/intra laboratory perception of the results, the development of computer-aided diagnosis (CAD) tools is used to support the decision. In this report, we propose the classification technique based on Artificial Neural Network (ANN) that can classify the Hep-2 cell images into 3 classes namely positive, negative and intermediate,specifically to determine the presence of antinuclear autoantibodies (ANA)

The strong gravitational lens finding challenge

Large-scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders of magnitudes beyond the number known today. Finding these rare objects will require picking them out of at least tens of millions of images, and deriving scientific results from them will require quantifying the efficiency and bias of any search method. To achieve these objectives automated methods must be developed. Because gravitational lenses are rare objects, reducing false positives will be particularly important. We present a description and results of an open gravitational lens finding challenge. Participants were asked to classify 100 000 candidate objects as to whether they were gravitational lenses or not with the goal of developing better automated methods for finding lenses in large data sets. A variety of methods were used including visual inspection, arc and ring finders, support vector machines (SVM) and convolutional neural networks (CNN). We find that many of the methods will be easily fast enough to analyse the anticipated data flow. In test data, several methods are able to identify upwards of half the lenses after applying some thresholds on the lens characteristics such as lensed image brightness, size or contrast with the lens galaxy without making a single false-positive identification. This is significantly better than direct inspection by humans was able to do. Having multi-band, ground based data is found to be better for this purpose than single-band space based data with lower noise and higher resolution, suggesting that multi-colour data is crucial. Multi-band space based data will be superior to ground based data. The most difficult challenge for a lens finder is differentiating between rare, irregular and ring-like face-on galaxies and true gravitational lenses. The degree to which the efficiency and biases of lens finders can be quantified largely depends on the realism of the simulated data on which the finders are trained

DustPedia: Multiwavelength photometry and imagery of 875 nearby galaxies in 42 ultraviolet-microwave bands

Aims. The DustPedia project is capitalising on the legacy of the Herschel Space Observatory, using cutting-edge modelling techniques to study dust in the 875 DustPedia galaxies – representing the vast majority of extended galaxies within 3000 km s-1 that were observed by Herschel. This work requires a database of multiwavelength imagery and photometry that greatly exceeds the scope (in terms of wavelength coverage and number of galaxies) of any previous local-Universe survey. Methods. We constructed a database containing our own custom Herschel reductions, along with standardised archival observations from GALEX, SDSS, DSS, 2MASS, WISE, Spitzer, and Planck. Using these data, we performed consistent aperture-matched photometry, which we combined with external supplementary photometry from IRAS and Planck. Results. We present our multiwavelength imagery and photometry across 42 UV-microwave bands for the 875 DustPedia galaxies. Our aperture-matched photometry, combined with the external supplementary photometry, represents a total of 21 857 photometric measurements. A typical DustPedia galaxy has multiwavelength photometry spanning 25 bands. We also present the Comprehensive & Adaptable Aperture Photometry Routine (CAAPR), the pipeline we developed to carry out our aperture-matched photometry. CAAPR is designed to produce consistent photometry for the enormous range of galaxy and observation types in our data. In particular, CAAPR is able to determine robust cross-compatible uncertainties, thanks to a novel method for reliably extrapolating the aperture noise for observations that cover a very limited amount of background. Our rich database of imagery and photometry is being made available to the community

What Is the Integrated Information Theory of Consciousness?

In the first instance, IIT is formulated as a theory of the physical basis of the 'degree' or ‘level’ or ‘amount’ of consciousness in a system. In addition, integrated information theorists have tried to provide a systematic theory of how physical states determine the specific qualitative contents of episodes of consciousness: for instance, an experience as of a red and round thing rather than a green and square thing. I raise a series of questions about the central explanatory target, the 'degree' or ‘level’ or ‘amount’ of consciousness. I suggest it is not at all clear what scientists and philosophers are talking about when they talk about consciousness as gradable. I also raise some questions about the explanation of qualitative content

Low resolution spectroscopy of ISOGAL sources: Search for early-type stars with infrared excess

An analysis of low resolution spectra and infared data of 29 ISOGAL-DENIS sources with mid-IR excess is presented. Eight ISOGAL sources from our sample with 7-15 micron excess are found to be B and A-type stars, some of them with emission lines. Two ISOGAL sources, J175614.4-240831 (B3-4IIIe) and J173845.3-312403 (B7III), show a bump between 5000 and 6000 Angstroem which maybe attributed to extended red emission (ERE). Some of the B,A and F-type giants with a large infrared excess might be in the post-AGB phase. For about 50% of the sources in this preliminary study, a nearby second (or even multiple) component was found. Such sources, in particular two B-stars, are not discussed when the probability of the optical spectrum being associated with the ISOGAL source is low. These results confirm that the DENIS-ISOGAL I-J/K-[15] diagram is the most suitable diagram to distinguish between early (AB) and late spectral types (KM). It provides the most useful tool to systematically search for nearby early-type stars with an infrared excess among the background of distant AGB stars in ISOGAL fields of the Galactic disk

Neural Information Processing: between synchrony and chaos

The brain is characterized by performing many different processing tasks ranging from elaborate processes such as pattern recognition, memory or decision-making to more simple functionalities such as linear filtering in image processing. Understanding the mechanisms by which the brain is able to produce such a different range of cortical operations remains a fundamental problem in neuroscience. Some recent empirical and theoretical results support the notion that the brain is naturally poised between ordered and chaotic states. As the largest number of metastable states exists at a point near the transition, the brain therefore has access to a larger repertoire of behaviours. Consequently, it is of high interest to know which type of processing can be associated with both ordered and disordered states. Here we show an explanation of which processes are related to chaotic and synchronized states based on the study of in-silico implementation of biologically plausible neural systems. The measurements obtained reveal that synchronized cells (that can be understood as ordered states of the brain) are related to non-linear computations, while uncorrelated neural ensembles are excellent information transmission systems that are able to implement linear transformations (as the realization of convolution products) and to parallelize neural processes. From these results we propose a plausible meaning for Hebbian and non-Hebbian learning rules as those biophysical mechanisms by which the brain creates ordered or chaotic ensembles depending on the desired functionality. The measurements that we obtain from the hardware implementation of different neural systems endorse the fact that the brain is working with two different states, ordered and chaotic, with complementary functionalities that imply non-linear processing (synchronized states) and information transmission and convolution (chaotic states)