YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

A comprehensive survey on computer vision based concepts,methodologies, analysis and applications for automatic gun/knife detection

The ability to detect gun and gun held in hand or other body parts is a typical human skill. The same problem presents an imperative task for computer vision system. Automatic observer independent detection of hand held gun or gun held in the other body part, whether it is visible or concealed, provides enhance security in vulnerable places and initiates appropriate action there. Compare to the automatic object detection systems, automatic detection of gun has very few successful attempts. In the present scope of this paper, we present an extensive survey on automatic detection of gun and define a taxonomy for this particular detection system. We also describe the inherent difficulties related with this problem. In this survey of published papers, we examine different approaches used in state-of-the-art attempts and compare performances of these approaches. Finally, this paper concludes pointing to the possible research gaps in related fields.     

基于Internet的远程教育系统模型研究

随着计算机网络技术的发展，远程教学系统的结构发生了重大的变化，逐步由原来的客户机／服务器(C／S)结构转变为基于Internet的浏览器／服务器(B／S)结构。本文提出了基于CORBA技术的B／S结构系统模型。分析了其运行过程，并与传统的结构进行了比较，指明了其优越性。在本文的结尾。指出了使用这种技术的一个具体例子。     

实验室的质量监督(上)

质量监督是实验室保持人员能力,进行自我完善,日常渐进的重要手段,是持续改进的重要组成部分,也是实验室管理工作的难点,本文给出质量监督的目的、对象、方法、记录等.     

结合RDF实现对XML文档的RBAC

文章提出了一种面向XML文档的基于XMLschema并结合RDF的访问控制模型,它实现了对XML文档的细粒度的安全访问控制,同时提供了对XML文档中associationsecurityobject的安全访问控制。     

Wavelength and Waveband Assignment for Ring Networks Based on Parallel Multi‐granularity Hierarchical OADMs

In this paper we study the optimization issues of ring networks employing novel parallel multi‐granularity hierarchical optical add‐drop multiplexers (OADMs). In particular, we attempt to minimize the number of control elements for the off‐line case. We present an integer linear programming formulation to obtain the lower bound in optimization, and propose an efficient heuristic algorithm called global bandwidth resource assignment that is suitable for the design of large‐scale OADM networks.     

基于对地观测激光回波特征的目标特性研究

本文研究了对地观测激光回波特征与地面目标特征之间的关系模型，分析了分类地面目标的激光回波特征，提出一种基于查表法的目标特性计算方法并给出了仿真结果。     

高功率脉冲水中放电的应用及其发展

首先介绍了高功率脉冲水下放电的机理，然后综合论述了其应用和研究的状况，从较为成熟的脉冲水处理技术到医疗领域的ESWL应用技术，以及在脉冲电场食品杀菌和水下目标探测方面的最新发展和研究，最后指出了高功率脉冲电技术应用前景以及进行更系统和深入研究的必要性。     

CDMA系统的网络优化

CDMA技术已经成为下一代移动通信的主流技术，CDMA网络的建设也初具规模。移动网络的优化则是实际运营过程中的一个重要环节。文中试图反映CDMA网络优化的一般原理，阐述了CDMA网络优化时需要考虑的几个主要问题，介绍了优化时需要调整的一些关键参数。