SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels

We present Spline-based Convolutional Neural Networks (SplineCNNs), a variant of deep neural networks for irregular structured and geometric input, e.g., graphs or meshes. Our main contribution is a novel convolution operator based on B-splines, that makes the computation time independent from the kernel size due to the local support property of the B-spline basis functions. As a result, we obtain a generalization of the traditional CNN convolution operator by using continuous kernel functions parametrized by a fixed number of trainable weights. In contrast to related approaches that filter in the spectral domain, the proposed method aggregates features purely in the spatial domain. In addition, SplineCNN allows entire end-to-end training of deep architectures, using only the geometric structure as input, instead of handcrafted feature descriptors. For validation, we apply our method on tasks from the fields of image graph classification, shape correspondence and graph node classification, and show that it outperforms or pars state-of-the-art approaches while being significantly faster and having favorable properties like domain-independence.Comment: Presented at CVPR 201

meV resolution in laser-assisted energy-filtered transmission electron microscopy

The electronic, optical, and magnetic properties of quantum solids are determined by their low-energy (< 100 meV) many-body excitations. Dynamical characterization and manipulation of such excitations relies on tools that combine nm-spatial, fs-temporal, and meV-spectral resolution. Currently, phonons and collective plasmon resonances can be imaged in nanostructures with sub-nm and 10s meV space/energy resolution using state-of-the-art energy-filtered transmission electron microscopy (TEM), but only under static conditions, while fs-resolved measurements are common but lack spatial or energy resolution. Here, we demonstrate a new method of spectrally resolved photon-induced near-field electron microscopy (SRPINEM) that allows us to obtain nm-fs-resolved maps of nanoparticle plasmons with an energy resolution determined by the laser linewidth (20 meV in this work), and not limited by electron beam and spectrometer energy spreading. This technique can be extended to any optically-accessible low-energy mode, thus pushing TEM to a previously inaccessible spectral domain with an unprecedented combination of space, energy and temporal resolution.Comment: 19 pages, 7 figure

The First Public Release of South Pole Telescope Data: Maps of a 95 deg^2 Field from 2008 Observations

The South Pole Telescope (SPT) has nearly completed a 2500 deg^2 survey of the southern sky in three frequency bands. Here, we present the first public release of SPT maps and associated data products. We present arcminute-resolution maps at 150 GHz and 220 GHz of an approximately 95 deg^2 field centered at R.A. 82°.7, decl. –55°. The field was observed to a depth of approximately 17 μK arcmin at 150 GHz and 41 μK arcmin at 220 GHz during the 2008 austral winter season. Two variations on map filtering and map projection are presented, one tailored for producing catalogs of galaxy clusters detected through their Sunyaev-Zel'dovich effect signature and one tailored for producing catalogs of emissive sources. We describe the data processing pipeline, and we present instrument response functions, filter transfer functions, and map noise properties. All data products described in this paper are available for download at http://pole.uchicago.edu/public/data/maps/ra5h30dec-55 and from the NASA Legacy Archive for Microwave Background Data Analysis server. This is the first step in the eventual release of data from the full 2500 deg^2 SPT survey

High Power Quantum Cascade Laser for Terahertz Imaging

Video rate or real-time imaging in the terahertz (THz) frequency range has become possible in the last few years with the advent of compact and high power THz sources, such as quantum cascade (QC) lasers, and the THz-sensitive vanadium oxide based microbolometer focal plane arrays. A new higher power QCL had been acquired and was characterized using FTIR spectroscopic techniques as part of this thesis. Spectral analysis revealed the center radiation frequency to be about 3.78 THz, which was close to the manufacturers specification. Relative power analysis showed significantly higher magnitude, of at least two orders, than the previous low power QCL. Significant temperature build-up of the cryostat, where the laser was mounted, was noticed in terms of a temperature rise of about 16 Kelvins, but was not detrimental to the laser performance. Active real-time THz imaging was conducted with the laser and a 160 x 120 element microbolometer focal plane array camera, FLIR A20M. The off-axis parabolic (OAP) reflective mirrors were re-configured for the imaging experiment to ensure sufficient THz energy would be focused onto the object. This optical setup could be easily re-configured for either transmission mode, as well as reflective mode imaging experiments. A synchronization circuitry was designed to synchronously modulate the QCL pulses with the focal plane array for differential imaging. This operation would eliminate unwanted signals from the infrared background, obviating the need for dedicated spectral filters that would have significantly attenuated the THz signal as well. Preliminary experiments showed better contrast in the acquired images. Post-processing algorithms such as addition of digital gain, enhanced edges, and integration of multiple images could potentially enhance the quality of the THz images, and extend the research towards reflective and stand-off THz imaging.http://archive.org/details/highpowerquantum109456845Civilian, DSO National Laboratories, Singapor

Cellular tracking in time-lapse phase contrast images

The quantitative analysis of live cells is a key issue in evaluating biological processes. The current clinical practice involves the application of a tedious and time consuming manual tracking procedure on large amount of data. As a result, automatic tracking systems are currently developed and evaluated. However, problems caused by cellular division, agglomeration, Brownian motion and topology changes are difficult issues that have to be accommodated by automatic tracking techniques. In this paper, we detail the development of a fully automated multi-target tracking system that is able to deal with Brownian motion and cellular division. During the tracking process our approach includes the neighbourhood relationship and motion history to enforce the cellular tracking continuity in the spatial and temporal domain. The experimental results reported in this paper indicate that our method is able to accurately track cellular structures in time-lapse data

Analysis of Different Filters for Image Despeckling : A Review

Digital image acquisition and processing in clinical diagnosis plays a significant part. Medical images at the time of acquisition can be corrupted via noise. Removal of this noise from images is a challenging problem. The presence of signal dependent noise is referred as speckle which degrades the actual quality of an image. Considering, several techniques have been developed focused on speckle noise reduction. The primary purpose of these techniques was to improve visualization of an image followed by preprocessing step for segmentation, feature extraction and registration. The scope of this paper is to provide an overview of despeckling techniques

A study of wavelet-based noise reduction techniques in mammograms

Breast cancer is one of the most common cancers and claims over one thousand lives every day. Breast cancer turns fatal only when diagnosed in late stages, but can be cured when diagnosed in its early stages. Over the last two decades, Digital Mammography has served the diagnosis of breast cancer. It is a very powerful aid for early detection of breast cancer. However, the images produced by mammography typically contain a great amount noise from the inherent characteristics of the imaging system and the radiation involved. Shot noise or quantum noise is the most significant noise which emerges as a result of uneven distribution of incident photons on the receptor. The X-ray dose given to patients must be minimized because of the risk of exposure. This noise present in mammograms manifests itself more when the dose of X-ray radiation is less and therefore needs to be treated before enhancing the mammogram for contrast and clarity. Several approaches have been taken to reduce the amount of noise in mammograms. This thesis presents a study of the wavelet-based techniques employed for noise reduction in mammograms --Abstract, page iii