In the real world, a realistic setting for computer vision or multimedia recognition problems is that we have some classes containing lots of training data and many classes contain a small amount of training data. Therefore, how to use frequent classes to help learning rare classes for which it is harder to collect the training data is an open question. Learning with Shared Information is an emerging topic in machine learning, computer vision and multimedia analysis. There are different level of components that can be shared during concept modeling and machine learning stages, such as sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, etc. Regarding the specific methods, multi-task learning, transfer learning and deep learning can be seen as using different strategies to share information. These learning with shared information methods are very effective in solving real-world large-scale problems. This special issue aims at gathering the recent advances in learning with shared information methods and their applications in computer vision and multimedia analysis. Both state-of-the-art works, as well as literature reviews, are welcome for submission. Papers addressing interesting real-world computer vision and multimedia applications are especially encouraged. Topics of interest include, but are not limited to:  • Multi-task learning or transfer learning for large-scale computer vision and multimedia analysis • Deep learning for large-scale computer vision and multimedia analysis • Multi-modal approach for large-scale computer vision and multimedia analysis • Different sharing strategies, e.g., sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, • Real-world computer vision and multimedia applications based on learning with shared information, e.g., event detection, object recognition, object detection, action recognition, human head pose estimation, object tracking, location-based services, semantic indexing. • New datasets and metrics to evaluate the benefit of the proposed sharing ability for the specific computer vision or multimedia problem. • Survey papers regarding the topic of learning with shared information.  Authors who are unsure whether their planned submission is in scope may contact the guest editors prior to the submission deadline with an abstract, in order to receive feedback.

IEEE transactions on pattern analysis and machine intelligence

Wearable or attachable health monitoring smart systems are considered to be the next generation of personal portable devices for remote medicine practices. Smart flexible sensing electronics are components crucial in endowing health monitoring systems with the capability of real-time tracking of physiological signals. These signals are closely associated with body conditions, such as heart rate, wrist pulse, body temperature, blood/intraocular pressure and blood/sweat bio-information. Monitoring such physiological signals provides a convenient and non-invasive way for disease diagnoses and health assessments. This Review summarizes the recent progress of flexible sensing electronics for their use in wearable/attachable health monitoring systems. Meanwhile, we present an overview of different materials and configurations for flexible sensors, including piezo-resistive, piezo-electrical, capacitive, and field effect transistor based devices, and analyze the working principles in monitoring physiological signals. In addition, the future perspectives of wearable healthcare systems and the technical demands on their commercialization are briefly discussed.

Flexible Sensing Electronics for Wearable/Attachable Health Monitoring

A family of nonlinear filters based on order statistics is presented. A mathematical tool derived through robust estimation theory, order statistics has allowed engineers to develop nonlinear filters with excellent robustness properties. These filters are well suited to digital image processing because they preserve the edges and the fine details of an image much better than conventional linear filters. The probabilistic and deterministic properties of the best known and most widely used filter in this family, the median filter, are discussed. In addition, the authors consider filters that, while not based on order statistics, are related to them through robust estimation theory. A table that ranks nonlinear filters under a variety of performance criteria is included. Most of the topics treated are very active research areas, and the applications are varied, including HDTV, multichannel signal processing of geophysical and ECG/EEG data, and a variety of telecommunications applications. >

/pdf/order-statistics-in-digital-image-processing-1rhdihn5hi.pdf

Order statistics in digital image processing

An implantable intraocular physiological sensor (e.g., 2000) for measuring a physiological characteristic, such as intraocular pressure. The implantable intraocular physiological sensor may include a tubular main body (2102) configured to house one or more electrical components. The implantable intraocular physiological sensor may also include a sensor cap (2108) configured to he inserted into a first end of the tubular main body with a moisture barrier seal. The implantable intraocular physiological sensor may wirelessly transmit measurements to an external device.

Intraocular physiological sensor

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Two Dimensional Signal And Image Processing

Demosaicking is an estimation process to determine missing color values when a single-sensor digital camera is used for color image capture. In this paper, we propose a number of new methods based on the application of Taylor series and cubic spline interpolation for color filter array demosaicking. To avoid the blurring of an edge, interpolants are first estimated in four opposite directions so that no interpolation is carried out across an edge. A weighted median filter, whose filter coefficients are determined by a classifier based on an edge orientation map, is then used to produce an output from the four interpolants to preserve edges. Using the proposed methods, the original color can be faithfully reproduced with minimal amount of color artifacts even at edges.

/pdf/color-filter-array-demosaicking-using-high-order-38ymexlufl.pdf

Color Filter Array Demosaicking Using High-Order Interpolation Techniques With a Weighted Median Filter for Sharp Color Edge Preservation

A novel median filter using analog tapped delay lines is designed for real-time signal processing. It requires only N+1 analog comparators for a window size of size N. As an extension, a general order-statistics filter can also be realized with moderate increase of circuit complexity. For current available fabrication technology for MOS switched-capacitor circuits, the filter can work at a clock rate up to 10 MHz. This development opens up possibilities for practical applications of nonlinear filtering in real-time signal processing, since the analog circuitry is far less complex than the corresponding digital circuitry. >

Analog implementation of median filter for real-time signal processing

With an ageing population showing an increasing prevalence of glaucoma, there is a pressing demand for continuous intraocular pressure (IOP) measurements which could surpass clinic-based measurements such as routine applanation tonometry. Glaucoma patients have fluctuations in IOP, and it has been proposed that these fluctuations are relevant to glaucoma progression. In addition, interindividual and intraindividual variation in corneal thickness and rigidity can lead to significant and poorly quantitated errors in applanation-based methods of estimating IOP. Microelectrical mechanical systems and complementary metal oxide semiconductor-based technology has enabled the development of smart miniaturised devices by augmenting the computational ability of microelectronics with capabilities of microsensors and microactuators. This review addresses various sensor technologies and both invasive and non-invasive approaches to the measurement of IOP. Advances in wireless communication (telemetry) between the implanted sensors and the external readout device are reviewed. In addition, biocompatibility of implantable sensors is discussed.

https://bjo.bmj.com/content/bjophthalmol/93/8/992.full.pdf

Advances in telemetric continuous intraocular pressure assessment

A 2-D, multishell median-based filter for real-time video signal processing is presented. The device is able to remove impulse and missing line noise in real-time without blurring sharp video images. A prototype using 75 standard transistor-transistor logic (TTL) chips has been realized on one single speedwire prototype board of size 17*30 cm/sup 2/ and its structure is suitable for VLSI implementation. The statistical performance of the nonlinear filter has been investigated and compared with that of standard 2-D median filters. It is shown that the filter has characteristics superior to those of its median-based counterparts while the hardware implementation is much simpler. >

A real-time 2-D median based filter for video signals

A novel noniterative extrapolation method based on Taylor series approximation is proposed for color filter array demosaicing. New extrapolation equations are derived for the estimation of the green plane with higher accuracy by including higher order terms of the Taylor series. Our proposed method avoids interpolation across an edge and thus reduces errors in the demosaiced image. It has been shown that our method outperforms other techniques in image quality measures, especially around edges.

Jim S. Jimmy Li

Papers

Color Filter Array Demosaicking Using High-Order Interpolation Techniques With a Weighted Median Filter for Sharp Color Edge Preservation

Analog implementation of median filter for real-time signal processing

Advances in telemetric continuous intraocular pressure assessment

A real-time 2-D median based filter for video signals

High order extrapolation using taylor series for color filter array demosaicing