An efficient filling algorithm for counting regions

Region filling has many applications in computer graphics and image analysis. Some region filling tasks can be performed by fast scan line filling algorithms. Other region filling tasks require seed filling algorithms which are more general but slower. This paper introduces a seed filling algorithm that is designed to count regions irrespective of their shape. The method is described and its performance is compared with three alternative algorithms by applying them to a collection of 34 test images. The four methods showed complete agreement with respect to the counted numbers of regions. The proposed method was found to be fastest and requiring least memory.     

An efficient approach to cyclic reference counting based on a coarse-grained search

Reference counting is known to have problems working with cyclic structures. In this paper, we present an efficient approach to cyclic reference counting, consisting of two key components. The first is a coarse-grained cycle collection algorithm that essentially performs a coarser (lightweight) analysis of the computation graph and thus greatly reduces the tracing cost (in comparison with the algorithms based on trial deletion to detect cycles). Our new cycle collector relies on this algorithm to obtain efficiency. Second, a predefined backup algorithm is incorporated to eliminate a theoretical problem that appears in the coarse-grained algorithm, thereby making the collector more practical. In this regard, we develop a heuristic based on the runtime behavior of the cycle collection to help the collector determine when to trigger the backup one. We have implemented and evaluated the proposed cycle collector on the Jikes RVM, where the SPECjvm98 benchmarks were applied. The results demonstrate that the novel approach is efficient and practical, compared to a modern cycle collector based on trial deletion.     

An efficient approach to cyclic reference counting based on a coarse-grained search

Reference counting is known to have problems working with cyclic structures. In this paper, we present an efficient approach to cyclic reference counting, consisting of two key components. The first is a coarse-grained cycle collection algorithm that essentially performs a coarser (lightweight) analysis of the computation graph and thus greatly reduces the tracing cost (in comparison with the algorithms based on trial deletion to detect cycles). Our new cycle collector relies on this algorithm to obtain efficiency. Second, a predefined backup algorithm is incorporated to eliminate a theoretical problem that appears in the coarse-grained algorithm, thereby making the collector more practical. In this regard, we develop a heuristic based on the runtime behavior of the cycle collection to help the collector determine when to trigger the backup one. We have implemented and evaluated the proposed cycle collector on the Jikes RVM, where the SPECjvm98 benchmarks were applied. The results demonstrate that the novel approach is efficient and practical, compared to a modern cycle collector based on trial deletion.     

An efficient Nash-implementation mechanism for network resource allocation

We propose a mechanism for auctioning bundles of multiple divisible goods in a network where buyers want the same amount of bandwidth on each link in their route. Buyers can specify multiple routes (corresponding to a source-destination pair). The total flow can then be split among these multiple routes. We first propose a one-sided VCG-type mechanism. Players do not report a full valuation function but only a two-dimensional bid signal: the maximum quantity that they want and the per-unit price they are willing to pay. The proposed mechanism is a weak Nash implementation, i.e., it has a non-unique Nash equilibrium that implements the social-welfare maximizing allocation. We show the existence of an efficient Nash equilibrium in the corresponding auction game, though there may exist other Nash equilibria that are not efficient. We then generalize this to arbitrary bundles of various goods. Each buyer submits a bid separately for each good but their utility function is a general function of allocations of bundles of various divisible goods. We then present a double-sided auction mechanism for multiple divisible goods. We show that there exists a Nash equilibrium of this auction game which yields the efficient allocation with strong budget balance.     

基于卷积神经网络的虫情图像分割和计数方法

为提高虫情图像的分割和计数的准确率,提出了一种基于卷积神经网络的虫情图像分割和计数方法。该方法基于U-Net模型构造了一种昆虫图像分割的模型Insect-Net,将完整的虫情图像和切割后的虫情图像分别输入模型后,提取两者特征进行融合。将融合后的特征输入1个1×1的卷积层得到最终分割结果,再将得到的结果二值化后,采用轮廓检测算法将昆虫目标与背景分离并计数。实验结果表明,该方法在虫情图像中取得了较高的分割正确率和计数正确率,分别为94.4%和89.2%。用深度学习和卷积神经网络的方法有效提高了虫情图像的计数精度,并且为昆虫识别分类提供了大量的无背景数据集。     

An efficient framework for counting pedestrians crossing a line using low-cost devices: the benefits of distilling the knowledge in a neural network

Multimedia Tools and Applications - In this paper, an efficient framework for counting pedestrians crossing a line of interest is proposed. Nowadays, the convolutional neural networks have very...     

An efficient CMAC neural network for stock index forecasting

Stock index forecasting is one of the major activities of financial firms and private investors in making investment decisions. Although many techniques have been developed for predicting stock index, building an efficient stock index forecasting model is still an attractive issue since even the smallest improvement in prediction accuracy can have a positive impact on investments. In this paper, an efficient cerebellar model articulation controller neural network (CAMC NN) is proposed for stock index forecasting. The traditional CAMC NN scheme has been successfully used in robot control due to its advantages of fast learning, reasonable generalization capability and robust noise resistance. But, few studies have been reported in using a CMAC NN scheme for forecasting problems. To improve the forecasting performance, this paper presents an efficient CMAC NN scheme. The proposed CMAC NN scheme employs a high quantization resolution and a large generalization size to reduce generalization error, and uses an efficient and fast hash coding to accelerate many-to-few mappings. The forecasting results and robustness evaluation of the proposed CMAC NN scheme were compared with those of a support vector regression (SVR) and a back-propagation neural network (BPNN). Experimental results from Nikkei 225 and Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) closing indexes show that the performance of the proposed CMAC NN scheme was superior to the SVR and BPNN models.     

An efficient cooperative exploration strategy for wireless sensor network

Wireless sensor networks (WSNs) are used in several applications such as healthcare devices, aerospace systems, automobile industry, security monitoring. However, WSNs have several challenges to improve the efficiency, robustness, failure tolerance and reliability of these sensors. Thus, cooperation between sensors is an important deal that increases sensor trust. Cooperative WSNs can be used to optimize the exploration of an unknown area in a distributed way. In this paper, the distributed Markovian model strategy that is used due to their past state-dependent reasoning. Moreover, the exploration strategy depends totally on the wireless communication protocol. Hence, in this paper, we propose an efficient cooperative strategy based on cognitive radio and software-defined radio which are promising technologies that increase spectral utilization and optimize the use of radio resources. We implement a distributed exploration strategy (DES) in mobile robots, and several experiments have been performed to localize targets while avoiding obstacles. Experiments were performed with several exploration robots. A comparison with another exploration strategy shows that DES improves the robots exploration.     

An efficient concurrent implementation of a neural network algorithm

The focus of this study is how we can efficiently implement the neural network backpropagation algorithm on a network of computers (NOC) for concurrent execution. We assume a distributed system with heterogeneous computers and that the neural network is replicated on each computer. We propose an architecture model with efficient pattern allocation that takes into account the speed of processors and overlaps the communication with computation. The training pattern set is distributed among the heterogeneous processors with the mapping being fixed during the learning process. We provide a heuristic pattern allocation algorithm minimizing the execution time of backpropagation learning. The computations are overlapped with communications. Under the condition that each processor has to perform a task directly proportional to its speed, this allocation algorithm has polynomial‐time complexity. We have implemented our model on a dedicated network of heterogeneous computers using Sejnowski's NetTalk benchmark for testing. Copyright © 2005 John Wiley & Sons, Ltd.     

Average up-sample network for crowd counting

Applied Intelligence - The task of crowd counting is receiving increased attention recently, but it still faces many challenges, such as extremely dense scene, scale variation and background...     

An efficient dynamic-identity based signature scheme for secure network coding

The network coding based applications are vulnerable to possible malicious pollution attacks. Signature schemes have been well-recognized as the most effective approach to address this security issue. However, existing homomorphic signature schemes for network coding either incur high transmission/computation overhead, or are vulnerable to random forgery attacks. In this paper, we propose a novel dynamic-identity based signature scheme for network coding by signing linear vector subspaces. The scheme can rapidly detect/drop the packets that are generated from pollution attacks, and efficiently thwart random forgery attack. By employing fast packet-based and generation-based batch verification approaches, a forwarding node can verify multiple received packets synchronously with dramatically reduced total verification cost. In addition, the proposed scheme provides one-way identity authentication without requiring any extra secure channels or separate certificates, so that the transmission cost can be significantly reduced. Simulation results demonstrate the practicality and efficiency of the proposed schemes.     

An efficient composition of Web services with active network support

Composition of Web services enables collaboration among autonomous business organisations such that they can integrate their services to perform collaborative business activities. It facilitates the development of new services using pre-existing Web services thus reducing development and operational costs. However, the highly distributed, dynamic, and autonomous nature of component Web services gives rise to various issues such as service matchmaking, reliability, availability, security and efficiency. This paper presents a new protocol in order to improve the efficiency of Web services composition. The proposed protocol is based on the peer-to-peer paradigm which exploits the capabilities of underlying networks such that part of the processing is carried out at the network nodes. Efficiency of the proposed protocol is tested through various experiments. Experimental results show that the proposed protocol significantly improves performance by reducing the system response time in the composition of Web services.     

基于层次划分的RP2P路由算法

RP2P路由算法将用于非结构化P2P网络中的随机邻居选择策略与结构化的分布式哈希表（DHT）环相结合,可在d跳内处理查询请求。但是,由于网络中的主机在网络带宽、内存、CPU等方面的能力差别很大,那些能力较弱的节点势必会影响整个系统的效率。利用网络中节点性能的差异,结合分层的概念,提出基于层次的RP2P路由算法,并对其性能进行了分析,算法在一定程度上缓解了网络中一部分节点的频繁加入和退出所引起的系统震荡。模拟实验表明,基于层次的RP2P路由算法有效提高了搜索的效率。     

An efficient composition of Web services with active network support

Composition of Web services enables collaboration among autonomous business organisations such that they can integrate their services to perform collaborative business activities. It facilitates the development of new services using pre-existing Web services thus reducing development and operational costs. However, the highly distributed, dynamic, and autonomous nature of component Web services gives rise to various issues such as service matchmaking, reliability, availability, security and efficiency. This paper presents a new protocol in order to improve the efficiency of Web services composition. The proposed protocol is based on the peer-to-peer paradigm which exploits the capabilities of underlying networks such that part of the processing is carried out at the network nodes. Efficiency of the proposed protocol is tested through various experiments. Experimental results show that the proposed protocol significantly improves performance by reducing the system response time in the composition of Web services.     

Context-aware pyramid attention network for crowd counting

Applied Intelligence - Achieving accurate crowd counting still faces many challenges due to continuous scale variations. To this end, we present an innovative Context-Aware Pyramid Attention...     

An efficient online citrus counting system for large-scale unstructured orchards based on the unmanned aerial vehicle

The accurate detection and counting of fruits in natural environments are key steps for the early yield estimation of orchards and the realization of smart orchard production management. However, existing citrus counting algorithms have two primary limitations: the performance of counting algorithms needs to be improved, and their system operation efficiency is low in practical applications. Therefore, in this paper, we propose a novel end-to-end orchard fruit counting pipeline that can be used by multiple unmanned aerial vehicles (UAVs) in parallel to help overcome the above problems. First, to obtain on-board camera images online, an innovative UAV live broadcast platform was developed for the orchard scene. Second, for this challenging specific scene, a detection network named Citrus-YOLO was designed to detect fruits in the video stream in real-time. Then, the DeepSort algorithm was used to assign a specific ID to each citrus fruit in the online UAV scene and track the fruits across video frames. Finally, a nonuniform distributed counter was proposed to correct the fruit count during the tracking process, and this can significantly reduce the counting errors caused by tracking failure. This is the first work to realize online and end-to-end counting in a field orchard environment. The experimental results show that the F1 score and mean absolute percentage error of the method are 89.07% and 12.75%, respectively, indicating that the system can quickly and accurately achieve fruit counting in large-scale unstructured citrus orchards. Although our work is discussed in the context of fruit counting, it can be extended to the detection, tracking and counting of a variety of other objects of interest in UAV application scenarios     

基于异或运算的机会网络高效转发策略

通过对机会网络中节点传递信息的方式进行研究分析,遍历可以通信的邻居节点,将两节点的信息作比较。通过交集的形式,选择节点中携带信息异或程度最大的邻居节点作为下一跳进行信息传递,从而形成一条有效性最大的通信路径。基于这样的分析过程,提出了一种基于异或运算的机会网络高效转发策略FSXO。通过与机会网络中的经典算法对比,仿真结果表明,FSXO策略能够在高传输成功率的情况下,减少网络中无效数据副本的存在,从而有效地降低路由开销,减少资源的消耗。