In this paper, we propose a scalable network for tiny object detection based on Faster RCNN. Compared with the previous feature extraction network, our network can be better applied to tiny objects. In the process of ...
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ISBN:
(纸本)9781538682463
In this paper, we propose a scalable network for tiny object detection based on Faster RCNN. Compared with the previous feature extraction network, our network can be better applied to tiny objects. In the process of feature extraction, the feature representation of large object will be strengthened, and the important tiny object information is ignored. By merging the feature maps output from different filters on the same layer, different sizes of targets will be captured. Then, not only considers the width of the network, but also realizes the deep integration of the network, which can avoid that the network is too deep to filter out tiny target information. Finally, by optimizing the algorithm for tiny objects based on deep learning, we achieved the best results with the accuracy rate of 34.1% on the Tsinghua-Tencent 100K.
In view of the problems of low efficiency and high cost of manual cloth loading,the introduction of loading robots has become a key strategy to improve the loading *** three-dimensional detection system was designed o...
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ISBN:
(纸本)9798350370010;9798350370003
In view of the problems of low efficiency and high cost of manual cloth loading,the introduction of loading robots has become a key strategy to improve the loading *** three-dimensional detection system was designed on the basis of the loading robot, and the hardware design and software demand analysis software were divided and designed. The system uses advanced 3D sensors as the core perception equipment, which is installed at the front end of the robot arm to realize the intelligent detection of environmental information in the truck compartment. Based on the TOF time-of-flight technology, high-quality point cloud data was obtained. In terms of point cloud processing, the normal estimation algorithm and the RANSAC circle fitting algorithm are proposed, which aim to optimize the quality of point cloud data, reduce noise, and accelerate the real-time processing *** can generate high-precision three-dimensional point cloud data, obtain the position and size of the detection carriage, and detect the loading status of the cloth, which can achieve higher speed and more accurate grasping and placing of the cloth, reduce the error, thereby significantly improving the overall loading efficiency and reducing labor costs.
Conjunctive Boolean query is one fundamental operation for document retrieval in many information systems and databases. In its most basic and popular form, a conjunctive query can be seen as the intersection problem ...
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ISBN:
(纸本)9781538636817
Conjunctive Boolean query is one fundamental operation for document retrieval in many information systems and databases. In its most basic and popular form, a conjunctive query can be seen as the intersection problem of multiple sets of sorted integers. Various algorithms have been put up in terms of maximizing the query efficiency. In recent years, researchers began to exploit the parallel advantage of single-instruction multiple-data (SIMD) instructions to accelerate the intersection procedure and achieved substantial gains over previous scalar algorithms. However, these works only focus on intersecting two sets at a time and ignore the scenario of multiple sets intersection. Missing from the literature is a thorough study that explores the combination of traditional multiple sets intersection algorithms and SIMD instructions. This article discusses software optimizations for the intersection algorithms via AVX2 and AVX512 SIMD instructions of modern processor architectures. Through an experimental analysis we show that the proposed is able to reduce comparisons executed while improving instruction throughput, thus gaining performance enhancement over previous methods.
Conjunctive Boolean query is one fundamental operation for document retrieval in many information systems and databases. Various algorithms have been put up in terms of maximizing the query efficiency. In recent years...
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ISBN:
(纸本)9781450349185
Conjunctive Boolean query is one fundamental operation for document retrieval in many information systems and databases. Various algorithms have been put up in terms of maximizing the query efficiency. In recent years, researchers began to exploit the parallel advantage of single-instruction-multiple-data (SIMD) instructions to accelerate the intersection procedure and achieved substantial gains over previous scalar algorithms. However, these works only focus on intersecting two sets at a time and ignore the scenario of multiple sets intersection. We present a flexible search algorithm which balances non-SIMD and SIMD comparisons in order to provide efficient and effective intersection.
The computational method of unconstrained optimization problem is an important research topic in the field of numerical computation. It is of great significance to solve the problem of unconstrained optimization. Ther...
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ISBN:
(纸本)9781467382670
The computational method of unconstrained optimization problem is an important research topic in the field of numerical computation. It is of great significance to solve the problem of unconstrained optimization. There are many ways that are applied to settle these questions, so we need to choose a method which owns much faster and less complex trait. Furthermore, in order to solve this rubs, this paper presents a comparative study of the common algorithms and our approach which are used to handle some concrete unconstrained optimization problems.
Content Aware Soft Real Time Media Broadcast (CASoRT) is a new solution for information service of cellular network. As the similar distribution of users interest, the data of same content may be accessed and retransm...
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ISBN:
(纸本)9781467309899
Content Aware Soft Real Time Media Broadcast (CASoRT) is a new solution for information service of cellular network. As the similar distribution of users interest, the data of same content may be accessed and retransmitted frequently in cellular network during certain period of time, which caused the dissipation of both energy and spectrum efficiency. With the development of Data Mining, the CASoRT system could discovers the users common interests and broadcast such content to users who may be interested in. With those users accessing the content locally, the potential retransmission could be avoided and thus it could save energy from carriers view while providing the same real time experience to the users. In this paper, we propose a set of algorithm for the optimization of broadcasting scheme for the CASoRT system to achieve more energy efficiency.
Investigation of hash join algorithm on multicore and many-core platforms showed that carefully tuned hash join implementations could outperform simple hash joins on most multi-core ***,hardware-oblivious hash join ha...
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Investigation of hash join algorithm on multicore and many-core platforms showed that carefully tuned hash join implementations could outperform simple hash joins on most multi-core ***,hardware-oblivious hash join has shown competitive performance on many-core *** Landing（KNL） has received attention in the field of parallel computing for its massively data-parallel nature and high memory bandwidth,but both hardwareoblivious and hardware-conscious hash join algorithms have not been systematically discussed and evaluated for KNL’s characteristics（high bandwidth,cluster mode,etc.）.In this paper,we present the design and implementation of the stateof-the-art hardware-oblivious and hardware-conscious hash joins that are tuned to exploit various KNL hardware *** a thorough evaluation,we show that:1) Memory allocation strategies based on KNL’s architecture are effective for both hardware-oblivious and hardware-conscious hash join algorithms;2) In order to improve the efficiency of the hash join algorithms,hardware architecture features are still non-negligible factors.
This paper provides algorithms for the optimization of autonomous hybrid systems based on the geometrical properties of switching manifolds. The first and second sections of the paper introduce optimal hybrid control ...
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ISBN:
(纸本)9781424477456
This paper provides algorithms for the optimization of autonomous hybrid systems based on the geometrical properties of switching manifolds. The first and second sections of the paper introduce optimal hybrid control systems and the third section deals with the analysis of the Hybrid Maximum Principle (HMP) algorithm introduced in [8]. The HMP algorithm in [8] is then extended to a geometrical algorithm by employing the notion of geodesic curves on switching manifolds. The convergence analysis for the proposed algorithm is based on Lasalle Theory. To reduce the computational burden, a simplified version of the geodesic algorithm is formulated in the local coordinate system of the switching state. Simulation results show a significant improvement in terms of convergence rate and stability compared with the HMP algorithm.
With rapid development in imaging modalities and computer power, computational model of cardiac electrophysiology field has been integrated with more and more powerful and sophisticated numerical solvers, which aims t...
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ISBN:
(纸本)9781538619377
With rapid development in imaging modalities and computer power, computational model of cardiac electrophysiology field has been integrated with more and more powerful and sophisticated numerical solvers, which aims to give people a more accurate understanding of the heart in pathological conditions. However, due to the limitation of the accuracy that the numerical methods could reach, the computational models may not yet be so accurate. In this paper, an implementation of Takeuchi-HL-1 unicellular model based on the first-order Euler method and the fourth-order Runge-Katta RK4 method is introduced. Besides accuracy, our work is also mainly focused on the optimization of data utilization based on the Runge-Kutta RK4 method. Through our work, it is shown that the higher order of accuracy method does give us a more accurate simulation result, while the time consumption is generally acceptable.
Currently, there is a high demand for neural network-based image compression codecs. These codecs employ non-linear transforms to create compact bit representations and facilitate faster coding speeds on devices compa...
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ISBN:
(纸本)9798331529543;9798331529550
Currently, there is a high demand for neural network-based image compression codecs. These codecs employ non-linear transforms to create compact bit representations and facilitate faster coding speeds on devices compared to the hand-crafted transforms used in classical frameworks. The scientific and industrial communities are highly interested in these properties, leading to the standardization effort of JPEG-AI. The JPEG-AI verification model has been released and is currently under development for standardization. Utilizing neural networks, it can outperform the classic codec VVC intra by over 10% BD-rate operating at base operation point. Researchers attribute this success to the flexible bit distribution in the spatial domain, in contrast to VVC intra's anchor that is generated with a constant quality point. However, our study reveals that VVC intra displays a more adaptable bit distribution structure through the implementation of various block sizes. As a result of our observations, we have proposed a spatial bit allocation method to optimize the JPEG-AI verification model's bit distribution and enhance the visual quality. Furthermore, by applying the VVC bit distribution strategy, the objective performance of JPEG-AI verification mode can be further improved, resulting in a maximum gain of 0.45 dB in PSNR-Y.
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