nils-herrmann/clean_scirepeval huggingface dataset:
Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption

We propose a privacy-preserving framework for learning visual classifiers by leveraging distributed private image data. This framework is designed to aggregate multiple classifiers updated locally using private data and to ensure that no private information about the data is exposed during and after its learning procedure. We utilize a homomorphic cryptosystem that can aggregate the local classifiers while they are encrypted and thus kept secret. To overcome the high computational cost of homomorphic encryption of high-dimensional classifiers, we (1) impose sparsity constraints on local classifier updates and (2) propose a novel efficient encryption scheme named doublypermuted homomorphic encryption (DPHE) which is tailored to sparse high-dimensional data. DPHE (i) decomposes sparse data into its constituent non-zero values and their corresponding support indices, (ii) applies homomorphic encryption only to the non-zero values, and (iii) employs double permutations on the support indices to make them secret. Our experimental evaluation on several public datasets shows that the proposed approach achieves comparable performance against state-of-the-art visual recognition methods while preserving privacy and significantly outperforms other privacy-preserving methods.
Visual learning and object verification with illumination invariance

This paper describes a method for recognizing partially occluded objects to realize a bin-picking task under different levels of illumination brightness by using the eigenspace analysis. In the proposed method, a measured color in the RGB color space is transformed into the HSV color space. Then, the hue of the measured color, which is invariant to change in illumination brightness and direction, is used for recognizing multiple objects under different levels of illumination conditions. The proposed method was applied to real images of multiple objects under different illumination conditions, and the objects were recognized and localized successfully.
Continuous 3D Label Stereo Matching Using Local Expansion Moves

We present an accurate stereo matching method using <italic>local expansion moves</italic> based on graph cuts. This new move-making scheme is used to efficiently infer per-pixel 3D plane labels on a pairwise Markov random field (MRF) that effectively combines recently proposed slanted patch matching and curvature regularization terms. The local expansion moves are presented as many <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math><alternatives> <inline-graphic xlink:href="taniai-ieq1-2766072.gif"/></alternatives></inline-formula>-expansions defined for small grid regions. The local expansion moves extend traditional expansion moves by two ways: localization and spatial propagation. By localization, we use different candidate <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math> <alternatives><inline-graphic xlink:href="taniai-ieq2-2766072.gif"/></alternatives></inline-formula>-labels according to the locations of local <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math><alternatives> <inline-graphic xlink:href="taniai-ieq3-2766072.gif"/></alternatives></inline-formula>-expansions. By spatial propagation, we design our local <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math><alternatives> <inline-graphic xlink:href="taniai-ieq4-2766072.gif"/></alternatives></inline-formula>-expansions to propagate currently assigned labels for nearby regions. With this localization and spatial propagation, our method can efficiently infer MRF models with a continuous label space using randomized search. Our method has several advantages over previous approaches that are based on fusion moves or belief propagation; it produces <italic>submodular moves </italic> deriving a <italic>subproblem optimality</italic>; it helps find good, smooth, piecewise linear disparity maps; it is suitable for parallelization; it can use cost-volume filtering techniques for accelerating the matching cost computations. Even using a simple pairwise MRF, our method is shown to have best performance in the Middlebury stereo benchmark V2 and V3.
Reflectance and Fluorescence Spectral Recovery via Actively Lit RGB Images

In recent years, fluorescence analysis of scenes has received attention in computer vision. Fluorescence can provide additional information about scenes, and has been used in applications such as camera spectral sensitivity estimation, 3D reconstruction, and color relighting. In particular, hyperspectral images of reflective-fluorescent scenes provide a rich amount of data. However, due to the complex nature of fluorescence, hyperspectral imaging methods rely on specialized equipment such as hyperspectral cameras and specialized illuminants. In this paper, we propose a more practical approach to hyperspectral imaging of reflective-fluorescent scenes using only a conventional RGB camera and varied colored illuminants. The key idea of our approach is to exploit a unique property of fluorescence: the chromaticity of fluorescent emissions are invariant under different illuminants. This allows us to robustly estimate spectral reflectance and fluorescent emission chromaticity. We then show that given the spectral reflectance and fluorescent chromaticity, the fluorescence absorption and emission spectra can also be estimated. We demonstrate in results that all scene spectra can be accurately estimated from RGB images. Finally, we show that our method can be used to accurately relight scenes under novel lighting.
Object recognition using local EGI and 3D models with M-estimators

A robot using a tele-operated system greatly reduces the demands on the human operator, although some human intervention is still required. In order to automate some of the robot's capabilities, we have developed a 3D object-localization method for the robot's positional adjustment. The method is designed to be insensitive to noise and outliers while, at the same time, it has optimal run-time efficiency. Our algorithm is general enough to be applied not only to our dual-armed mobile robots but also to other tele-operation robots. This paper first describes our algorithm, and then presents the performance evaluation.
Localization of insulators in electric distribution systems by using 3D template matching from multiple range images

Kyushu Electric has developed a dual-armed mobile-robot for use in electricity distribution systems. Although some human intervention is still required, the robot greatly reduces the demands on the human operator. In order to automate some of the robot's capabilities, we have developed a 3D object-localization method for robot positional adjustment. The method is designed to be insensitive to noise and outliers while, at the same time, it has optimal run-time efficiency. The paper first describes our algorithm, and then presents a performance evaluation.
Spherical harmonics vs. Haar wavelets: basis for recovering illumination from cast shadows

The problem of estimating an illumination distribution from images is called inverse lighting. For inverse lighting, three approaches have been developed based on specular reflection components, diffuse reflection components, and cast shadows. The present study provides theoretical insights as to why the approach based on cast shadows works in a reliable manner, and discusses what kind of basis functions are appropriate to be used for recovering illumination from cast shadows. First, we formalize the approach based on cast shadows by using spherical harmonics. Then, we analyze the approach in the frequency domain and show the advantages and the limitations of the approach. Second, motivated by the observations in the frequency domain, we propose an efficient method using Haar wavelets that provide compact supports and sparsity of coefficients. Finally, we report the results of experiments that compared the method using spherical harmonics and the method using Haar wavelets.
Structure and Magnetic Properties of CoNi Thin Films Epitaxially Grown on MgO(100) and SrTiO $_{3}$(100) Substrates

CoNi epitaxial thin films were prepared on MgO(100) and SrTiO3(100) single-crystal substrates by ultra-high vacuum molecular beam epitaxy. Effects of substrate temperature on the structural and magnetic properties of epitaxial films were investigated. On MgO(100) substrate, CoNi epitaxial films consisting of hcp(112¿0) and fcc(100) crystals are obtained whereas on SrTiO3(100) substrate, CoNi(100) single-crystal films with fcc structure are formed. CoNi film growth on both substrates seems to follow the Volmer-Weber mode. CoNi (100)fcc single-crystal film with smaller strain is obtained on SrTiO3 substrate rather than on MgO(100) substrate. The film strain decreases with increasing the substrate temperature. The magnetic hysteresis loops of CoNi epitaxial thin films reflect the magnetocrystalline anisotropies of hcp-CoNi and fcc-CoNi crystals.
Decoding of convolutional codes by Viterbi blind algorithm

For decoding of convolutional codes by the Viterbi algorithm, the knowledge of channel parameters on non-Gaussian channels is either essential or preferable. When the considered channel is fast time-varying, reliable and robust estimation of the channel parameters by the conventional decision-directed adaptive algorithms is hardly possible. In the present paper, the Viterbi algorithm is applied in a modified way. Firstly a new trellis diagram is constructed at the receiver side according to modified definitions of trellis state and branch. Secondly a new branch metric is defined so that its expression does not explicitly depend on the channel parameters. With these modifications, decoding can be achieved without the knowledge of channel parameters. This method provides a robust alternative for decoding of convolutional codes on fast fading (especially frequency-selective) channels where the estimation of channel parameters becomes more and more difficult.<<ETX>>
Stability issues in recovering illumination distribution from brightness in shadows

The paper describes a robust method for estimating, in a reliable manner, the illumination distribution of a real scene from shadows in a given image. In general, shadows in a scene are caused by the occlusion of incoming light; image brightness inside shadows have great potential for providing distinct clues to the illumination distribution of the scene. Taking advantage of this fact, we recently proposed to estimate the illumination distribution of a real scene from a single image of the scene. The proposed method has been applied successfully to real images with complex illumination distributions. Nevertheless, it was found that sometimes the method failed to provide a correct estimate of illumination distribution. Those failures stem from the fact that the method does not take into account several factors regarding the stability of illumination estimation. The study analyzes how much information is obtainable from a given image about the illumination distribution of the scene. In particular, we carefully examine the source of instability of using shadows obtained from a single image for the estimation in several aspects: blocked view of shadows by the object; limited sampling resolution for image brightness inside shadows; and the appropriate light model to approximate the illumination distribution of the scene. Based on this analysis, we propose a method that guarantees to reliably estimate the illumination distribution of a scene, regardless of the type of input image.
Bispectral photometric stereo based on fluorescence

We propose a novel technique called bispectral photometric stereo that makes effective use of fluorescence for shape reconstruction. Fluorescence is a common phenomenon occurring in many objects from natural gems and corals, to fluorescent dyes used in clothing. One of the important characteristics of fluorescence is its wavelength-shifting behavior: fluorescent materials absorb light at a certain wavelength and then reemit it at longer wavelengths. Due to the complexity of its emission process, fluorescence tends to be excluded from most algorithms in computer vision and image processing. In this paper, we show that there is a strong similarity between fluorescence and ideal diffuse reflection and that fluorescence can provide distinct clues on how to estimate an object's shape. Moreover, fluorescence's wavelength-shifting property enables us to estimate the shape of an object by applying photometric stereo to emission-only images without suffering from specular reflection. This is the significant advantage of the fluorescence-based method over previous methods based on reflection.
An electromagnetic system for magnetic microbead's manipulation

This paper presents the design of a magnetic micromanipulation system for wireless control of a single magnetic bead. Six orthogonally aligned electromagnetic coils were used to generate the magnetic fields for the manipulation and modeling equations were developed to evaluate the required inputs for each coil for precise closed-loop control of the magnetic bead. FEM simulation was performed to analyze the magnetic flux density and magnetic field gradient of the system and the results were compared with the actual measurement. To examine the performance of the proposed system, a super-paramagnetic microbead was placed in a salt medium and experiments were conducted to demonstrate the movements of the bead. The result suggests the ability of manipulating microbeads via the proposed magnetic manipulation system for various micro- and submicrometer scale applications.
Genetic algorithm approach to the configuration of wavelet packet processing tree

The standard wavelet transform can be considered to be a subtree of a complete multiresolution binary tree, in which each branch corresponds to a decomposition step. Any subtree of this multiresolution tree which covers all leaves is a valid wavelet packet processing tree, which specifies the processing steps for a wavelet decomposition of the original data. The present paper describes an adaptation scheme for configuring a wavelet packet processing tree using a genetic algorithm search of the complete multiresolution tree. Data compression is used as the target signal processing task. Trees are configured for different compression rates, and performance is measured based on the reconstruction distortion. Performances are validated using testing as well as training data; the performance of the configured trees are compared to that of the standard wavelet transform.
Dual-arm micromanipulation and handling of objects through visual images

Pick-and-place of micro-scale objects is essential for many microscopic tasks. For more sophisticated tasks, grasping and manipulating objects with two independent tools can enhance the capability and the dexterity of the tools. In this work, a dual-arm micromanipulation system equipped with two tungsten probes was employed for the manipulation of a sphere. In order to provide sufficient contact area for grasping, the two probes were positioned side-by-side to grasp a sphere lying on a glass substrate. Visual images were used to provide feedback for manipulating the sphere from one location to the desired location, finally releasing the sphere. Since the adhesion force is dominant in the micro-scale environment, the sphere adheres to the probe and could not be released. To resolve this issue, the two probes were reconfigured after the manipulation. The contact points of the two probes were reconfigured from a side-by-side contact, to a tip-to-tip contact with the sphere. Experimental results confirmed that through this probe reconfiguration, the success rate of sphere release from the probes is higher, allowing improved throughput with such an approach.
Illumination mipmaps for texture mapping in computational video

In computational video, acquired images are often texture mapped to blend with computer generated polygonal surfaces. The shading of a polygonal surface changes as the light source direction relative to the composite object changes due, for instance, to the object's motion. We propose the use of so-called illumination mipmaps that can adjust the texture mapped image according to the illumination change so that the appearance of the composite object is more cohesive. We test our concept on texture mapped images of human faces.
Applications of binary neural networks learning to pattern classification

This paper considers the use of binary neural networks for pattern classification. An expand-and-truncate learning (ETL) algorithm is used to determine the required number of neurons as well as the connecting weights in a three-layered feedforward network for classifying input patterns. The ETL algorithm is guaranteed to find a network for any binary-to-binary mappings. The ETL algorithm's performance in pattern classification is tested using a breast cancer database that have been used for benchmarking performance other machine learning methods. The ETL algorithm decomposes an arbitrarily linearly nonseparable function into multiple linearly separable functions, each of which is realized by a neuron in the hidden layer. ETL first finds the required hyperplanes for the given patterns, based on a geometrical analysis of the given patterns. The weights and thresholds are determined based on these identified hyperplanes. Depending on the given training patterns, the required number of neurons in the hidden layer will be determined by ETL.<<ETX>>
Conductive, multilayer scaffold with micro-porous structure for tissue engineering

Polymeric materials have been used extensively for the fabrication of various biomedical devices. In this paper, polydimethylsiloxane (PDMS) was adopted as the biomaterial to construct a porous, conductive nanocomposite scaffold for tissue regeneration. This proposed conductive scaffold will incorporate dielectrophoresis to manipulate cells towards the scaffold body for efficient cell seeding. In order to enhance the cell attachment onto the scaffold, microscale pores were also integrated throughout the scaffold surface in addition to the existing porous architecture from the scaffold geometry. Experiments were conducted to characterize the material properties of the proposed scaffold material and examine the improvement on the cell seeding process.
Design and Realization of Data Warehouse for Coastal Restoration

The goal of this paper is to propose a practical data warehouse model for the coastal restoration analysis. Coastal restoration practitioners are developing new and innovative ways to increase the efficiency and success of restoration efforts. These new methods range considerably in their scale of application, from addressing small, site-specific issues, to having a larger, regional or national focus. The proposed design of the data warehouse improves the decision capabilities of the existing independent coastal restoration decision support systems. The unified model also allows flexibility of adding new restoration projects in future. In this paper, we first try to identify the data warehousing design implications, and propose a multidimensional spatial model that supports the analyses. We then present sample queries, and define measures by which the coastal restoration data model can be evaluated
MEMS capacitive force sensor for use in microassembly

This paper presents the design and modeling of a MEMS capacitive sensor for use in microassembly processes. Force monitoring is an important aspect in microassembly processes. It can be used to control the movement of the microgripper to properly engage with and release the micropart without physical damages due to excessive force. In this paper, the proposed sensor structure has an overall dimension of 3600 mum times 840 mum times 10 mum and was fabricated using the Micragem fabrication process. A displacement reduction mechanism is incorporated in this sensor design to increase the sensitivity of the sensor. Experimental results showed that a capacitance change of 112.4 fF would result for a 20-mum input displacement.
Halftoning for color-indexed displays

In many applications, the color bit-depth of an image has to be modified, typically lowered, to match the rendering device. Halftoning is typically used to reduce the effects of quantization, which can produce objectionable contouring effects. Until now, color-indexed images whose palette was a subset of the colors of the image could only be dithered using error diffusion. We present an algorithm for color halftoning when the color palette is image-dependent. Experimental results demonstrate that our new algorithm does not introduce color shifts, color spikes, or wormy textures, and has greater preservation of detail.
On the configuration of multilayered feedforward networks by an evolutionary process

A learning algorithm based on genetic algorithms to configure multilayered feedforward networks in supervised learning mode is described. The method described lets a population of hidden units compete among themselves and "sell" themselves to be connected to members of another pool of output units. An output unit in this sense therefore represents a team comprising the output unit itself and its connected hidden units. This "team", of course, defines the architecture of the network. If each output unit can choose for itself how many hidden units it needs to accomplish the classification task, different architectures can be seen to be competing against each other. Experiment results are presented and discussed.
Image segmentation by multisensor data-fusion

The information content of an image is determined by the dynamic range of the sensor and the characteristics of the signal being recorded by the sensor. The integration of information from images from different types of sensors poses several interesting subproblems that are handled in a hierarchical manner. The authors place their discussion of these problems in the context of image segmentation. Integration may take place at various levels, ranging from pixel level to logical concepts such as features, objects, and scenes. The authors give an account of their initial efforts in dealing with sensor fusion for object recognition, and they study the aspects of image segmentation in the context of sensor fusion.<<ETX>>
A Visual Model-based Halftone Pattern Design Algorithm

A genetic algorithm approach to the design of dither matrices used in the dispersed-dot digital halftoning method is described. Digital halftoning techniques are used to render continuoustone images on high resolution binary display devices. The dispersed-dot methods are an important class of digital halftoning techniques that map gray levels in an image into specific binary patterns. The design of such patterns to reduce visible artifacts is important so as to render the image with higher fidelity. A design approach based on shaping the spectrum of the dithering signal according to a model of the human visual system is presented. The design process is formulated as an optimization problem, which is solved by a genetic algorithm. Theoretical upper bounds to the performance are derived and the genetic algorithm generally finds solutions that are within 90% of the upper bounds. The dither matrices that are found by the new algorithm are used to render a number of example images.
An online group-buying model based on fuzzy theory

Group buying is becoming an increasing important trend for electronic marketplaces. In order to enhance purchase willingness of customers, there is a need to adopt the concept of the bargaining in online group-buying. This research is solved through on process of generating offers by a fuzzy inference system. Three bargaining strategies found in the literature are used in forming strategies of pricing mechanism. Experimental results indicate that our model can be accepted and is used again by most customers. Moreover, the increase bargaining strategy is the most satisfying for customers.