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1.
电力企业智能招聘系统对电力企业招贤纳才,提高电力企业市场竞争力具有至关重要的作用。本文将卷积神经网络作用于智能招聘系统原始图像,采用K均值聚类算法对图像进行识别,同时对招聘系统的用户管理模块、信息检索模块、求职管理模块以及安全验证模块进行了设计与实现。将深度学习的经典算法卷积神经网络应用于智能招聘系统中使得智能招聘系统的安全性、智能性得到了很大程度的提升,对智能招聘系统的设计具有一定的实用价值。  相似文献   
2.
随着科学技术的快速发展与进步,当今社会要求学生学习知识水平越来越高,要求其学习范围更为广泛。因此目前学生仅依凭英语课堂学习还远远不够,很多时候根本无法适应社会发展的需要,所以培养学生自学能力就显得非常重要。由此提出开发一款英语自学系统为英语爱好者提供自学英语平台。文章立足于Web网络,依托B/C结构,应用ASP.NET和数据库进行相互融入技术;然后从功能模块,数据库等设计详细分析本系统设计;最后从聊天室、BBS论坛、以及留言板等方面来实现本系统的在线沟通与交流,从而完成了本系统研究。该系统不但能使学生学习英语不受时空限制,而且对于提升他们学习英语效果与使用英语能力均有很大帮助。  相似文献   
3.
Recently, a number of classification techniques have been introduced. However, processing large dataset in a reasonable time has become a major challenge. This made classification task more complex and expensive in calculation. Thus, the need for solutions to overcome these constraints such as field programmable gate arrays (FPGAs). In this paper, we give an overview of the various classification techniques. Then, we present the existing FPGA based implementation of these classification methods. After that, we investigate the confronted challenges and the optimizations strategies. Finally, we highlight the hardware accelerator architectures and tools for hardware design suggested to improve the FPGA implementation of classification methods.  相似文献   
4.
Tracking-by-detection (TBD) is a significant framework for visual object tracking. However, current trackers are usually updated online based on random sampling with a probability distribution. The performance of the learning-based TBD trackers is limited by the lack of discriminative features, especially when the background is full of semantic distractors. We propose an attention-driven data augmentation method, in which a residual attention mechanism is integrated into the TBD tracking network as supplementary references to identify discriminative image features. A mask generating network is used to simulate changes in target appearances to obtain positive samples, where attention information and image features are combined to identify discriminative features. In addition, we propose a method for mining hard negative samples, which searches for semantic distractors with the response of the attention module. The experiments on the OTB2015, UAV123, and LaSOT benchmarks show that this method achieves competitive performance in terms of accuracy and robustness.  相似文献   
5.
Calmodulin (CaM) is an important intracellular protein that binds Ca2+ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca2+ concentration through interactions with CaM.  相似文献   
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7.
Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels.  相似文献   
8.
针对分割神经网络需要大量的高质量标签但较难获取的问题,提出基于3D scSE-UNet的半监督学习分割方法. 该方法使用自训练的半监督学习框架,将包含改进的并行空间/特征通道压缩和激励模块(scSE-block+)的3D scSE-UNet作为分割网络. scSE-block+可以从图像空间和特征通道2个方面自动学习图像的有效特征,抑制无用冗余特征,更好地保留图像边缘信息. 在自训练过程中加入全连接条件随机场,对分割网络产生的伪标签进行边缘细化,提升伪标签的精确度. 在LiTS17 Challenge和SLIVER07数据集上验证所提出方法的有效性. 当有标签图像占训练集总图像的30%时,所提方法的Dice相似系数(dice score)为0.941. 结果表明,所提出的半监督学习分割方法可以在仅使用少量标注数据的情况下,取得与全监督分割方法相当的分割效果,有效减轻肝脏CT图像分割对专家标注数据的依赖.  相似文献   
9.
A Quantitative Critical Thinking (QCT) software tool was developed in this study to facilitate students’ learning of quantitative critical thinking via repeated practice by chemical engineering students reading a core module called fluid-solid systems. The software tool generated detailed calculation steps to typical engineering design problems encountered in this module that contained weaknesses, flaws or even errors. Students utilized the software tool to practice identifying these weaknesses, flaws or errors in the design solutions and then present a better or correct design by applying the concepts and knowledge acquired in the module. Since the QCT software tool was built upon an existing design software tool that was able to generate the correct, detailed design calculation steps to design problems, students were able to check their own design calculations against those presented by the software tool during this second learning step, thereby engaging in and learning quantitative critical thinking via a repeated practice approach. The software tool was successful in enhancing the performance of second-year undergraduate students in solving a question that required quantitative critical thinking in the final examination of the module. The average percentage scores achieved by students for the question who reported higher frequencies of usage of the software were generally higher than those who reported lower frequencies of usage or did not utilize the software tool throughout the semester.  相似文献   
10.
针对密集观测场景下敏捷成像卫星任务规划问题求解空间大、输入任务序列较长的特点,综合考虑时间窗口约束、任务转移时卫星姿态调整时间、存储约束和电量约束,对敏捷成像卫星任务规划问题进行建模. 提出融合IndRNN和Pointer Networks的算法模型(Ind-PN)对敏捷成像卫星任务规划问题进行求解,使用多层的IndRNN结构作为算法模型的解码器. 基于Pointer Networks机制对输入任务序列进行选择,使用Mask向量考虑敏捷成像卫星任务规划问题中的各类约束. 基于Actor Critic强化学习算法对算法模型进行训练,以获得最大的观测收益率. 实验结果表明,对于密集观测场景下的任务规划,Ind-PN算法的收敛速度更快,可以获得更高的观测收益率.  相似文献   
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