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Routing is an essential stage in physical design, where already placed components are connected by wires. Routing must satisfy various manufacturing requirements, referred to as design rules. We formalize the problem of design-rule-aware routing and introduce a solver, called DRouter, for the resulting problem. Plain routing is often modeled as follows: given an undirected weighted graph and a set...
Sparse Coding is a widely used method to represent an image. However, sparse coding and its improved algorithms have the problem of complex computation and long running time and so on. For these problems, we propose an image classification method based on hash codes and space pyramid, which encodes local feature points with hash codes instead of sparse coding. Firstly, extract the local feature points...
In a series of studies, articulatory features used as speech attributes for automatic speech recognition systems have been shown to improve the performance. The existing articulatory features are defined by phonetician as a set of articulatory descriptions of phones, which represent some semantic information explaining how humans produce speech sounds via the interaction of different physiological...
This paper addresses the problem of creating simplifiers for logic formulas based on conditional term rewriting. In particular, the paper focuses on a program synthesis application where formula simplifications have been shown to have a significant impact. We show that by combining machine learning techniques with constraint-based synthesis, it is possible to synthesize a formula simplifier fully...
This paper presents an audio/speech coding algorithm using the matching pursuit with the dynamic dictionary forming based on wavelet packet decomposition and its performance evaluation. The proposed methodology for selecting the most relevant wavelet coefficients is based on maximizing the matching between the auditory excitation scalograms associated with the original and the modeled signal correspondingly...
We consider the problem of learning graphs in a sparse multiclass support vector machines framework. For such a problem, sparse graph penalty is useful to select the significant features and interpret the results. Classical ℓ1-norm learns a sparse solution without considering the structure between the features. In this paper, a structural knowledge is encoded as directed acyclic graph and a graph...
There are a large number of image super resolution algorithms based on the sparse coding, and some algorithms realize multi-frame super resolution. For utilizing multiple low resolution observations, both accurate image registration and sparse coding are required. Previous study on multi-frame super resolution based on sparse coding firstly apply block matching for image registration, followed by...
Transfer of power over a wireless channel has gained popularity. However, transfer of data along with power is a useful prospect. This can be a solution to many obstacles in the field of robotics. We propose a system module, comprising a transmitter and receiver circuit, for the same and elucidate the parameters and techniques involved in their optimization. This paper primarily deals with experimental...
This paper concerns minimizing the expected distortion of a Gaussian source, transmitted over a two-hop block fading channel, under the mean square-error measure. It is assumed that there is not a direct link between the source and destination, and a simple Decode and Forward (DF) relay, handles the communication. The channel state information (CSI) associated with each hop is available at the corresponding...
Recent studies have shown the potential performance gain of Non Uniform Constellations (NUC) compared to the conventional uniform constellations. NUC can be a promising candidate in 5G systems to increase the data throughput. In the literature, NUC is designed for a specific SNR value and propagation channel. However, in broadcast/multicast services, the received signal by different users will see...
Rate-distortion optimization (RDO) plays an important part in improving the coding efficiency of High Efficiency Video Coding (HEVC), especially for the hierarchical coding structure defined in the Random-Access (RA) configuration, noted as Random-Access Hierarchical Video Coding (RA-HVC), where different frames are assigned to different temporal layers and further coded with different coding parameters...
In this paper, we present a novel perceptually-based optimization for the improvement of stereoscopic video coding efficiency. The main idea of this proposed scheme is to adaptively adjust the quantization parameter by taking into account the Human Visual System perceptual characteristics. For this, a saliency map is generated from both views and then segmented into salient and non-salient regions...
Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. Inspired by this observation, we propose a novel method to explicitly and simultaneously learn a set of common patterns as well as class-specific features for classification. Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific)...
In this paper, we present a novel classification model which combines the convolutional sparse coding framework with the classification strategy. In the training phase, the proposed model trained a convolutional filter bank by all images of each class. In the test phase, the label of test image is determined by all convolutional filter banks. Compared with canonical sparse representation and dictionary...
This paper addresses the problem of designing a global tone mapping operator for rate-distortion optimized backward compatible compression of HDR images. We consider a two layer coding scheme in which a base SDR layer is coded with HEVC, inverse tone mapped and subtracted from the input HDR signal to yield the enhancement HDR layer. The tone mapping curve design is formulated as the minimization of...
The latest high efficiency video coding (HEVC) standard achieves about 50% bit-rate reduction at equivalent visual quality compared to H.264/AVC. Sample adaptive offset (SAO) is one of the newly adopted tools right after deblocking filter, which can improve both coding efficiency and visual quality. However, for real-time encoding scenarios, the complexity of SAO is usually too high to be enabled...
Earlier research has shown the efficacy of using geometry discontinuities, encoded using “breakpoints,” in improving the coding efficiency of piecewise smooth media, such as depth maps and motion flows. This work proposes a new structure for encoding these breakpoints that is more suited for piecewise affine media, such as affine motion flows. Here, we choose to employ belief propagation over a graphical...
This paper presents a novel algorithm that aims at minimizing the required decoding energy by exploiting a general energy model for HEVC-decoder solutions. We incorporate the energy model into the HEVC encoder such that it is capable of constructing a bit stream whose decoding process consumes less energy than the decoding process of a conventional bit stream. To achieve this, we propose to extend...
We address the problem of optimizing block-coded motion parameters for use inside typical motion-compensating video encoders. We cast the given discrete problem as a nonsmooth nonconvex optimization problem which is defined over some graph, and solve it using the split primal-dual hybrid gradient algorithm. Although computational efficiency is not the main focus of this paper, an efficient, parallelized...
This paper presents efficient SIMD optimizations for the open-source Kvazaar HEVC intra encoder. The C implementation of Kvazaar is accelerated by Intel AVX2 instructions whose effect on Kvazaar ultrafast preset is profiled. According to our profiling results, C functions of SATD, DCT, quantization, and intra prediction account for over 60% of the total intra coding time of Kvazaar ultrafast preset...
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