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The extraction of multi-attribute objects from the deep web is the bridge between the unstructured web and structured data. Existing approaches either induce wrappers from a set of human-annotated pages or leverage repeated structures on…

Databases · Computer Science 2012-10-23 Tim Furche , Georg Gottlob , Giovanni Grasso , Giorgio Orsi , Christian Schallhart , Cheng Wang

Deep learning has revolutionized the field of hyperspectral image (HSI) analysis, enabling the extraction of complex spectral and spatial features. While convolutional neural networks (CNNs) have been the backbone of HSI classification,…

The cost and accuracy of simulating complex physical systems using the Finite Element Method (FEM) scales with the resolution of the underlying mesh. Adaptive meshes improve computational efficiency by refining resolution in critical…

Hyperspectral neutron tomography is an effective method for analyzing crystalline material samples with complex compositions in a non-destructive manner. Since the counts in the hyperspectral neutron radiographs directly depend on the…

We propose a computationally efficient wrapper feature selection method - called Autoencoder and Model Based Elimination of features using Relevance and Redundancy scores (AMBER) - that uses a single ranker model along with autoencoders to…

Machine Learning · Computer Science 2020-01-03 Sharan Ramjee , Aly El Gamal

We adapt the remote sensing-inspired AMBER model from multi-band image segmentation to 3D medical datacube segmentation. To address the computational bottleneck of the volumetric transformer, we propose the AMBER-AFNO architecture. This…

Image and Video Processing · Electrical Eng. & Systems 2026-04-21 Andrea Dosi , Semanto Mondal , Rajib Chandra Ghosh , Massimo Brescia , Giuseppe Longo

In this paper, a new deep learning architecture for stereo disparity estimation is proposed. The proposed atrous multiscale network (AMNet) adopts an efficient feature extractor with depthwise-separable convolutions and an extended cost…

Computer Vision and Pattern Recognition · Computer Science 2019-04-22 Xianzhi Du , Mostafa El-Khamy , Jungwon Lee

A new method for the analysis of the scattering rates from angle-resolved photoelectron spectroscopy (ARPES) is presented and described in details. It takes into account experimental instrumental resolution and finite temperature effects.…

Strongly Correlated Electrons · Physics 2022-02-04 R. Kurleto , J. Fink

The Abundance Matching Box for the Epoch of Reionization (AMBER) is a semi-numerical code for modeling the cosmic dawn. The new algorithm is not based on the excursion set formalism for reionization, but takes the novel approach of…

Cosmology and Nongalactic Astrophysics · Physics 2022-05-12 Hy Trac , Nianyi Chen , Ian Holst , Marcelo A. Alvarez , Renyue Cen

Ambient backscatter communication (AmBC) is becoming increasingly popular for enabling green communication amidst the continual development of the Internet-of-things paradigm. Efforts have been put into backscatter signal detection as the…

Signal Processing · Electrical Eng. & Systems 2020-08-25 Xiyu Wang , Hüseyin Yiğitler , Riku Jäntti

Existing approaches for image-based Automatic Meter Reading (AMR) have been evaluated on images captured in well-controlled scenarios. However, real-world meter reading presents unconstrained scenarios that are way more challenging due to…

Computer Vision and Pattern Recognition · Computer Science 2021-05-13 Rayson Laroca , Alessandra B. Araujo , Luiz A. Zanlorensi , Eduardo C. de Almeida , David Menotti

Americium-beryllium (AmBe), a well-known tagged neutron source, is commonly used for evaluating the neutron detection efficiency of detectors used in ultralow background particle physics experiments, such as reactor neutrino and diffuse…

Instrumentation and Detectors · Physics 2023-09-29 Hiroshi Ito , Kohei Wada , Takatomi Yano , Yota Hino , Yuga Ommura , Masayuki Harada , Akihiro Minamino , Masaki Ishitsuka

Neutron reflectometry (NR) is a powerful technique to probe surfaces and interfaces. NR is inherently an indirect measurement technique, access to the physical quantities of interest (layer thickness, scattering length density, roughness),…

The first astrophysical results of the VLTI focal instrument AMBER have shown the importance of the differential and closure phase measures, which are supposed to be much less sensitive to atmospheric and instrumental biases than the…

Astrophysics · Physics 2009-11-13 Florentin Millour , Romain Petrov , Martin Vannier , Stefan Kraus

Many engineering systems require accurate simulations of complex physical systems. Yet, analytical solutions are only available for simple problems, necessitating numerical approximations such as the Finite Element Method (FEM). The cost…

A conceptual scheme of a hybrid-emulsion spectrometer for investigating various channels of neutrino oscillations is proposed. The design emphasizes detection of $\tau$ leptons by detached vertices, reliable identification of electrons, and…

High Energy Physics - Experiment · Physics 2009-10-31 A. E. Asratyan , G. V. Davidenko , A. G. Dolgolenko , V. S. Kaftanov , M. A. Kubantsev , V. S. Verebryusov

We present in this paper an innovative data reduction method for single-mode interferometry. It has been specifically developed for the AMBER instrument, the three-beam combiner of the Very Large Telescope Interferometer, but can be derived…

Astrophysics · Physics 2009-11-11 E. Tatulli , the AMBER consortium

Spectroastrometry measures source astrometry as a function of wavelength/velocity. Reverberations of spectroastrometric signals naturally arise in broad-line regions (BLRs) of active galactic nuclei (AGNs) as a result of the continuum…

Astrophysics of Galaxies · Physics 2023-01-31 Yan-Rong Li , Jian-Min Wang

Neutron grating interferometry is an advanced method in neutron imaging that allows the simultaneous recording of the transmission, the differential phase and the dark-field image. Especially the latter has recently received high interest…

Materials Science · Physics 2016-10-10 Tommy Reimann , Sebastian Mühlbauer , Michael Horisberger , Peter Böni , Michael Schulz

To backpropagate the gradients through stochastic binary layers, we propose the augment-REINFORCE-merge (ARM) estimator that is unbiased, exhibits low variance, and has low computational complexity. Exploiting variable augmentation,…

Machine Learning · Statistics 2019-09-11 Mingzhang Yin , Mingyuan Zhou
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