Inkball Models as Features for Handwriting Recognition

Inkball models provide a tool for matching and comparison of spatially structured markings such as handwritten characters and words. Hidden Markov models offer a framework for decoding a stream of text in terms of the most likely sequence of causal states. Prior work with HMM has relied on observation of features that are correlated with underlying characters, without modeling them directly. This paper proposes to use the results of inkball-based character matching as a feature set input directly to the HMM. Experiments indicate that this technique outperforms other tested methods at handwritten word recognition on a common benchmark when applied without normalization or text deslanting

Technology roadmap for cold-atoms based quantum inertial sensor in space

Recent developments in quantum technology have resulted in a new generation of sensors for measuring inertial quantities, such as acceleration and rotation. These sensors can exhibit unprecedented sensitivity and accuracy when operated in space, where the free-fall interrogation time can be extended at will and where the environment noise is minimal. European laboratories have played a leading role in this field by developing concepts and tools to operate these quantum sensors in relevant environment, such as parabolic flights, free-fall towers, or sounding rockets. With the recent achievement of Bose-Einstein condensation on the International Space Station, the challenge is now to reach a technology readiness level sufficiently high at both component and system levels to provide "off the shelf"payload for future generations of space missions in geodesy or fundamental physics. In this roadmap, we provide an extensive review on the status of all common parts, needs, and subsystems for the application of atom-based interferometers in space, in order to push for the development of generic technology components

Design of a dual species atom interferometer for space

Atom interferometers have a multitude of proposed applications in space including precise measurements of the Earth's gravitational field, in navigation & ranging, and in fundamental physics such as tests of the weak equivalence principle (WEP) and gravitational wave detection. While atom interferometers are realized routinely in ground-based laboratories, current efforts aim at the development of a space compatible design optimized with respect to dimensions, weight, power consumption, mechanical robustness and radiation hardness. In this paper, we present a design of a high-sensitivity differential dual species $^{85}$Rb/$^{87}$Rb atom interferometer for space, including physics package, laser system, electronics and software. The physics package comprises the atom source consisting of dispensers and a 2D magneto-optical trap (MOT), the science chamber with a 3D-MOT, a magnetic trap based on an atom chip and an optical dipole trap (ODT) used for Bose-Einstein condensate (BEC) creation and interferometry, the detection unit, the vacuum system for $10^{-11}$ mbar ultra-high vacuum generation, and the high-suppression factor magnetic shielding as well as the thermal control system. The laser system is based on a hybrid approach using fiber-based telecom components and high-power laser diode technology and includes all laser sources for 2D-MOT, 3D-MOT, ODT, interferometry and detection. Manipulation and switching of the laser beams is carried out on an optical bench using Zerodur bonding technology. The instrument consists of 9 units with an overall mass of 221 kg, an average power consumption of 608 W (819 W peak), and a volume of 470 liters which would well fit on a satellite to be launched with a Soyuz rocket, as system studies have shown.Comment: 30 pages, 23 figures, accepted for publication in Experimental Astronom

STE-QUEST - Test of the Universality of Free Fall Using Cold Atom Interferometry

In this paper, we report about the results of the phase A mission study of the atom interferometer instrument covering the description of the main payload elements, the atomic source concept, and the systematic error sources

Technology roadmap for cold-atoms based quantum inertial sensor in space

Recent developments in quantum technology have resulted in a new generation of sensors for measuring inertial quantities, such as acceleration and rotation. These sensors can exhibit unprecedented sensitivity and accuracy when operated in space, where the free-fall interrogation time can be extended at will and where the environment noise is minimal. European laboratories have played a leading role in this field by developing concepts and tools to operate these quantum sensors in relevant environment, such as parabolic flights, free-fall towers, or sounding rockets. With the recent achievement of Bose–Einstein condensation on the International Space Station, the challenge is now to reach a technology readiness level sufficiently high at both component and system levels to provide “off the shelf” payload for future generations of space missions in geodesy or fundamental physics. In this roadmap, we provide an extensive review on the status of all common parts, needs, and subsystems for the application of atom-based interferometers in space, in order to push for the development of generic technology components

Camera-based sudoku recognition with deep belief network

In this paper, we propose a method to detect and recognize a Sudoku puzzle on images taken from a mobile camera. The lines of the grid are detected with a Hough transform. The grid is then recomposed from the lines. The digits position are extracted from the grid and finally, each character is recognized using a Deep Belief Network (DBN). To test our implementation, we collected and made public a dataset of Sudoku images coming from cell phones. Our method proved successful on our dataset, achieving 87.5% of correct detection on the testing set. Only 0.37% of the cells were incorrectly guessed. The algorithm is capable of handling some alterations of the images, often present on phone-based images, such as distortion, perspective, shadows, illumination gradients or scaling. On average, our solution is able to produce a result from a Sudoku in less than 100ms

Mixed handwritten and printed digit recognition in Sudoku with convolutional deep belief network

In this paper, we propose a method to recognize Sudoku puzzles containing both handwritten and printed digits from images taken with a mobile camera. The grid and the digits are detected using various image processing techniques including Hough Transform and Contour Detection. A Convolutional Deep Belief Network is then used to extract high-level features from raw pixels. The features are finally classified using a Support Vector Machine. One of the scientific question addressed here is about the capability of the Deep Belief Network to learn extracting features on mixed inputs, printed and handwritten. The system is thoroughly tested on a set of 200 Sudoku images captured with smartphone cameras under varying conditions, e.g. distortion and shadows. The system shows promising results with 92% of the cells correctly classified. When cell detection errors are not taken into account, the cell recognition accuracy increases to 97.7%. Interestingly, the Deep Belief Network is able to handle the complex conditions often present on images taken with phone cameras and the complexity of mixed printed and handwritten digits

On CPU performance optimization of restricted Boltzmann machine and convolutional RBM

Although Graphics Processing Units (GPUs) seem to currently be the best platform to train machine learning models, most research laboratories are still only equipped with standard CPU systems. In this paper, we investigate multiple techniques to speedup the training of Restricted Boltzmann Machine (RBM) models and Convolutional RBM (CRBM) models on CPU with the Contrastive Divergence (CD) algorithm. Experimentally, we show that the proposed techniques can reduce the training time by up to 30 times for RBM and up to 12 times for CRBM, on a data set of handwritten digits