计算机视觉检测论文范文

推荐下计算机视觉这个领域，依据学术范标准评价体系得出的近年来最重要的9篇论文吧： （对于英语阅读有困难的同学，访问后可以使用翻译功能） 一、Deep Residual Learning for Image Recognition  摘要：Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitly reformulate the layers as learning residual functions with reference to the layer inputs, instead of learning unreferenced functions. We provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth. On the ImageNet dataset we evaluate residual nets with a depth of up to 152 layers—8× deeper than VGG nets [40] but still having lower complexity. An ensemble of these residual nets achieves error on the ImageNet test set. This result won the 1st place on the ILSVRC 2015 classification task. We also present analysis on CIFAR-10 with 100 and 1000 layers. The depth of representations is of central importance for many visual recognition tasks. Solely due to our extremely deep representations, we obtain a 28% relative improvement on the COCO object detection dataset. Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions1, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation. 全文链接： 文献全文 - 学术范 () 二、Very Deep Convolutional Networks for Large-Scale Image Recognition 摘要：In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evaluation of networks of increasing depth using an architecture with very small (3x3) convolution filters, which shows that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 weight layers. These findings were the basis of our ImageNet Challenge 2014 submission, where our team secured the first and the second places in the localisation and classification tracks respectively. We also show that our representations generalise well to other datasets, where they achieve state-of-the-art results. We have made our two best-performing ConvNet models publicly available to facilitate further research on the use of deep visual representations in computer vision. 全文链接： 文献全文 - 学术范 () 三、U-Net: Convolutional Networks for Biomedical Image Segmentation 摘要：There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available annotated samples more efficiently. The architecture consists of a contracting path to capture context and a symmetric expanding path that enables precise localization. We show that such a network can be trained end-to-end from very few images and outperforms the prior best method (a sliding-window convolutional network) on the ISBI challenge for segmentation of neuronal structures in electron microscopic stacks. Using the same network trained on transmitted light microscopy images (phase contrast and DIC) we won the ISBI cell tracking challenge 2015 in these categories by a large margin. Moreover, the network is fast. Segmentation of a 512x512 image takes less than a second on a recent GPU. The full implementation (based on Caffe) and the trained networks are available at . 全文链接： 文献全文 - 学术范 () 四、Microsoft COCO: Common Objects in Context 摘要：We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding. This is achieved by gathering images of complex everyday scenes containing common objects in their natural context. Objects are labeled using per-instance segmentations to aid in precise object localization. Our dataset contains photos of 91 objects types that would be easily recognizable by a 4 year old. With a total of million labeled instances in 328k images, the creation of our dataset drew upon extensive crowd worker involvement via novel user interfaces for category detection, instance spotting and instance segmentation. We present a detailed statistical analysis of the dataset in comparison to PASCAL, ImageNet, and SUN. Finally, we provide baseline performance analysis for bounding box and segmentation detection results using a Deformable Parts Model. 全文链接： 文献全文 - 学术范 () 五、Rethinking the Inception Architecture for Computer Vision 摘要：Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmarks. Although increased model size and computational cost tend to translate to immediate quality gains for most tasks (as long as enough labeled data is provided for training), computational efficiency and low parameter count are still enabling factors for various use cases such as mobile vision and big-data scenarios. Here we are exploring ways to scale up networks in ways that aim at utilizing the added computation as efficiently as possible by suitably factorized convolutions and aggressive regularization. We benchmark our methods on the ILSVRC 2012 classification challenge validation set demonstrate substantial gains over the state of the art: 21:2% top-1 and 5:6% top-5 error for single frame evaluation using a network with a computational cost of 5 billion multiply-adds per inference and with using less than 25 million parameters. With an ensemble of 4 models and multi-crop evaluation, we report 3:5% top-5 error and 17:3% top-1 error on the validation set and 3:6% top-5 error on the official test set. 全文链接： 文献全文 - 学术范 () 六、Mask R-CNN 摘要：We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance. The method, called Mask R-CNN, extends Faster R-CNN by adding a branch for predicting an object mask in parallel with the existing branch for bounding box recognition. Mask R-CNN is simple to train and adds only a small overhead to Faster R-CNN, running at 5 fps. Moreover, Mask R-CNN is easy to generalize to other tasks, ., allowing us to estimate human poses in the same framework. We show top results in all three tracks of the COCO suite of challenges, including instance segmentation, bounding-box object detection, and person keypoint detection. Without tricks, Mask R-CNN outperforms all existing, single-model entries on every task, including the COCO 2016 challenge winners. We hope our simple and effective approach will serve as a solid baseline and help ease future research in instance-level recognition. Code will be made available. 全文链接： 文献全文 - 学术范 () 七、Feature Pyramid Networks for Object Detection 摘要：Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid representations have been avoided in recent object detectors that are based on deep convolutional networks, partially because they are slow to compute and memory intensive. In this paper, we exploit the inherent multi-scale, pyramidal hierarchy of deep convolutional networks to construct feature pyramids with marginal extra cost. A top-down architecture with lateral connections is developed for building high-level semantic feature maps at all scales. This architecture, called a Feature Pyramid Network (FPN), shows significant improvement as a generic feature extractor in several applications. Using a basic Faster R-CNN system, our method achieves state-of-the-art single-model results on the COCO detection benchmark without bells and whistles, surpassing all existing single-model entries including those from the COCO 2016 challenge winners. In addition, our method can run at 5 FPS on a GPU and thus is a practical and accurate solution to multi-scale object detection. Code will be made publicly available. 全文链接： 文献全文 - 学术范 () 八、ORB: An efficient alternative to SIFT or SURF 摘要：Feature matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods rely on costly descriptors for detection and matching. In this paper, we propose a very fast binary descriptor based on BRIEF, called ORB, which is rotation invariant and resistant to noise. We demonstrate through experiments how ORB is at two orders of magnitude faster than SIFT, while performing as well in many situations. The efficiency is tested on several real-world applications, including object detection and patch-tracking on a smart phone. 全文链接： 文献全文 - 学术范 () 九、DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs 摘要：In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First , we highlight convolution with upsampled filters, or ‘atrous convolution’, as a powerful tool in dense prediction tasks. Atrous convolution allows us to explicitly control the resolution at which feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge the field of view of filters to incorporate larger context without increasing the number of parameters or the amount of computation. Second , we propose atrous spatial pyramid pooling (ASPP) to robustly segment objects at multiple scales. ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales. Third , we improve the localization of object boundaries by combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling and downsampling in DCNNs achieves invariance but has a toll on localization accuracy. We overcome this by combining the responses at the final DCNN layer with a fully connected Conditional Random Field (CRF), which is shown both qualitatively and quantitatively to improve localization performance. Our proposed “DeepLab” system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching percent mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online. 全文链接： 文献全文 - 学术范 () 希望对你有帮助！

不管是导师还是读者，评判论文的第一感是先审核题目，选题是撰写论文的奠基工程，在一定程度上决定着论文的优劣。下面我给大家带来2021各方向硕士论文题目写作参考，希望能帮助到大家!

计算机硕士论文题目选题参考

1、基于特征提取的图像质量评价及计算机辅助诊断

2、多功能体育馆音质控制计算机仿真实例对比研究

3、中职计算机应用基础课游戏化学习软件的设计研究

4、基于图像的计算机物体识别研究

5、中职计算机生态课堂高效教学策略的实践性研究

6、基于计算机视觉的胶囊缺陷检测系统的设计与实现

7、计算机网络信息安全风险评估标准与 方法 研究

8、基于计算机视觉的表面缺陷检测及应用

9、擦窗机伸缩臂计算机辅助设计系统研究

10、基于乳腺癌计算机辅助诊断的病理图像分析

11、面向创新创业的民办高校计算机基础课程教学改革研究

12、中职学校计算机类课程作业提交与评价系统研究

13、基于物联网的计算机监控系统设计与开发

14、基于计算机视觉的皮革测配色研究

15、基于计算机视觉的杂草种子鉴别

16、基于计算机视觉的花卉分级系统研究

17、计算机辅助景观表现研究

18、基于计算机视觉的水面智能监控研究

19、计算机辅助飞机铆钉连接优化设计

20、非相似平台管理计算机的余度管理技术研究

21、基于图像形状特征量的计算机辅助肝硬化检测研究

22、乳腺肿瘤超声剪切波弹性图像的计算机辅助诊断

23、面向老龄用户的计算机界面交互模式研究

24、培养中职计算机网络专业学生综合实践能力的 措施 研究

25、基于动态部分可重构FPGA的计算机组成原理实验平台设计

26、三值光学计算机解码器中并行感光阵列的设计

27、基于中国虹计算机的文件管理系统设计与研究

28、计算机网络虚拟实验教学平台的设计与实现

29、基于计算机视觉的油菜生长过程自动识别研究

30、基于计算机视觉的火焰三维重建算法的研究

31、企业内网计算机终端软件补丁管理系统的研究与设计

32、治安监控中基于计算机视觉的异常行为检测技术研究

33、集成无线体域网穿戴式计算机设计

34、基于计算机视觉的疲劳驾驶检测技术研究

35、基于MRI的肝脏病变计算机辅助诊断

36、基于模糊认知图的计算机在线证据智能分析技术研究

37、基于录像分析的高职计算机微课设计的案例研究

38、动态可重构穿戴计算机软件平台的设计与实现

39、计算机视觉中可变特征目标检测的研究与应用

40、基于计算机视觉的单体猪喘气行为视频特征表达方法研究

41、基于计算机视觉的指针式电表校验的关键技术研究

42、基于计算机视觉的车牌识别系统的算法研究

43、乐山计算机学校学生管理系统设计与实现

44、基于计算机视觉微测量技术研究

45、基于计算机视觉的枸杞分级方法研究

46、基于计算机视觉的外膜厚度测量方法的研究

47、基于计算机视觉的车道偏离预警算法研究

48、节能监管计算机联网多参数计量控制系统

49、点状开发建设项目水土保持方案计算机辅助编制系统研发

50、大学计算机课程实验教学平台的设计与实现

51、肠癌计算机辅助识别算法的研究

52、计算机联锁安全关键软件可靠性设计

53、计算机视觉在织物疵点自动检测中的应用研究

54、数字水印技术在计算机辅助评卷系统中的应用研究

教育 硕士论文题目

1、帮助学生掌握数学解题策略的实验与研究

2、中学数学合情推理教学现状调查和分析

3、中小学数学估算的教与学

4、培养中专生数学应用能力的研究

5、中美高中课程标准下数学探究的比较研究

6、 高中数困生良好数学思维品质培养研究

7、高一学生数学概括能力培养的实验 研究

8、网络环境下高中数学教学模式研究

9、新课标下促进学生数学学习正迁移的研究

10、基于新课程的初中数学自主学习课堂教学的实践与研究

11、中学生对数学公式的记忆特点研究

12、TI-92技术在高中数学新课程算法教学中的应用

13、数学史在中学数学教育中的教学价值

14、在数学教学中，指导学生掌握数学学习策略的实践研究

15、全国高考试题与高中数学竞赛试题相关性研究

16、新课程下初中数学学习过程评价的实验与研究

17、职高《数学》课程探究性学习的实践研究

18、培养数学学习迁移能力的课堂教学策略

19、在高中数学学习中自我监控能力培养策略的研究

20、中专班《数学实验》选修课的研究与实践

21、初中生数学思维过程的研究及数学思维能力的培养

22、培养高中生数学直觉思维能力的途径

23、论现行初中数学课堂练习及单元测验的改革

24、网络环境下“中学数学实验课”教学设计与评价的实践研究

25、高一学生函数概念学习障碍及教学对策

26、师范生数学语言表达能力的实验研究

27、职业中学数学教学中融入数学史教学的实践研究

28、高中数学教学中小组合作学习的实践与研究

29、高中数学新课程《球面上的几何》的教学实验与研究

30、数学发现法教学的课堂实施研究

31、开展初中“ 反思 性数学学习”的研究与实践

32、初中数学新课程下小组合作学习的研究与实验

33、以“教学反思”为载体的小学数学教师培训的研究

34、技校兴趣缺乏型数困生的现状及教学研究

35、中学数学课堂探究式教学模式的理论和实践研究

36、数学交流探究

37、论数学课程的情感与态度目标

38、数学课堂探究性教学的理论与实践研究

39、中学数学教师评价研究

40、五年一贯制师范数学课程设置研究

41、 高二数学 优秀生与学困生的解题策略比较研究

42、建构主义及其观点下的《全日制义务教育数学课程标准》(初中部分)解析

43、新课程标准下弗赖登塔尔数学教学原则在我国小学及初中低年级数学教学中的应用构想

44、在高中数学教学中运用《几何画板》进行数学实验的探索与实践

45、数学历史名题作为研究性学习的开发与实验研究

46、普通高中几何课程体系实施研究

47、中学数学中非语言表征的应用研究

软件工程专业硕士论文题目

1、 城轨线网数据标准与数据库设计研究

2、 基于秘密共享协议的移动数据库研究

3、 云环境下数据库同步服务的研究与实现

4、 列数据库SQL语言编译器的研究与实现

5、 面向复杂负载特征和性能需求的云数据库弹性动态平衡问题研究

6、 数据资源规划中主题数据库划分研究

7、 某某后方仓库综合数据库管理系统设计与实现

8、 SYBASE数据库的索引压缩的设计与实现

9、 分布式数据库中间件DBScale的设计与实现

10、 PostgreSQL数据库中SSD缓存模块的设计与实现

11、 数据库工具DBTool的设计与实现

12、 基于大型数据库的智能搜索与摘要提取技术研究

13、 基于用户行为分析与识别的数据库入侵检测系统的研究

14、 面向内存数据库的快照机制和持久性支持研究

15、 面向海量高并发数据库中间件的研究与应用

16、 CUBRID数据库自动化测试框架的设计与实现

17、 KingbaseES数据库列存储测试的设计与实现

18、 网络数据库服务质量监测系统的设计与实现

19、 外包数据库完整性验证的研究

20、 云南省宗教基础数据库系统的研究与分析

21、 基于SQL Server数据库的银行 保险 数据管理系统的设计和实现

22、 邮政金融电子稽查系统的数据库设计与实现

23、 文档型数据库的存储模型设计和研究

24、 多数据库环境电子商务信息安全技术研究

25、 多数据库环境数据集成与转换技术研究

26、 应用于网络监控系统的数据库设计与实现研究

27、 车辆特征数据库管理系统设计与实现

28、 数据库共享容灾技术应用研究

29、 非关系数据库加密模型的研究

30、 “数据库原理课程”在线评卷系统的设计与实现

31、 基于日志挖掘的数据库入侵检测方法研究

32、 内存数据库在城市垃圾监控系统中的研究与应用

33、 基于B/S结构的数据库加密技术的研究与应用

34、 省级基础水文数据库的设计与实现

35、 多数据库系统数据仓库集成技术应用研究

36、 多数据库环境下数据迁移技术的研究与应用

37、 基于J2EE数据库业务系统代码生成工具的设计与实现

38、 基于智能设备的嵌入式数据库安全性研究

39、 基于药用动物图像数据库的设计与实现

40、 地震预警地质构造条件数据库管理系统的设计与实现

各方向硕士论文题目写作参考相关 文章 ：

★ 文学硕士论文的写作技巧

★ 心理学类论文大全及写作指导

★ 教育方向专业毕业论文题目有哪些

★ 论文写作格式

★ 硕士论文写作格式要求

★ 大学生论文题目参考2021

★ 经济学毕业论文题目参考2021

★ 大学学科论文范文及写作指导

★ 毕业论文写作心得5篇

★ 硕士论文写作指导方法及要求