PP-GAN:Style Transfer from Korean Portraits to ID Photos Using Landmark Extractor with GAN

The objective of style transfer is to maintain the content of an image while transferring the style of another image.However,conventional methods face challenges in preserving facial features,especially in Korean portraits where elements like the“Gat”(a traditional Korean hat)are prevalent.This paper proposes a deep learning network designed to perform style transfer that includes the“Gat”while preserving the identity of the face.Unlike traditional style transfer techniques,the proposed method aims to preserve the texture,attire,and the“Gat”in the style image by employing image sharpening and face landmark,with the GAN.The color,texture,and intensity were extracted differently based on the characteristics of each block and layer of the pre-trained VGG-16,and only the necessary elements during training were preserved using a facial landmark mask.The head area was presented using the eyebrow area to transfer the“Gat”.Furthermore,the identity of the face was retained,and style correlation was considered based on the Gram matrix.To evaluate performance,we introduced a metric using PSNR and SSIM,with an emphasis on median values through new weightings for style transfer in Korean portraits.Additionally,we have conducted a survey that evaluated the content,style,and naturalness of the transferred results,and based on the assessment,we can confidently conclude that our method to maintain the integrity of content surpasses the previous research.Our approach,enriched by landmarks preservation and diverse loss functions,including those related to“Gat”,outperformed previous researches in facial identity preservation.

Robust ACO-Based Landmark Matching and Maxillofacial Anomalies Classification

Imagery assessment is an efficient method for detecting craniofacial anomalies.A cephalometric landmark matching approach may help in orthodontic diagnosis,craniofacial growth assessment and treatment planning.Automatic landmark matching and anomalies detection helps face the manual labelling lim-itations and optimize preoperative planning of maxillofacial surgery.The aim of this study was to develop an accurate Cephalometric Landmark Matching method as well as an automatic system for anatomical anomalies classification.First,the Active Appearance Model(AAM)was used for the matching process.This pro-cess was achieved by the Ant Colony Optimization(ACO)algorithm enriched with proximity information.Then,the maxillofacial anomalies were classified using the Support Vector Machine(SVM).The experiments were conducted on X-ray cephalograms of 400 patients where the ground truth was produced by two experts.The frameworks achieved a landmark matching error(LE)of 0.50±1.04 and a successful landmark matching of 89.47%in the 2 mm and 3 mm range and of 100%in the 4 mm range.The classification of anomalies achieved an accuracy of 98.75%.Compared to previous work,the proposed approach is simpler and has a comparable range of acceptable matching cost and anomaly classification.Results have also shown that it outperformed the K-nearest neigh-bors(KNN)classifier.

Landmarks-Driven Triplet Representation for Facial Expression Similarity

The facial landmarks can provide valuable information for expression-related tasks.However,most approaches only use landmarks for segmentation preprocessing or directly input them into the neural network for fully connection.Such simple combination not only fails to pass the spatial information to network,but also increases calculation amounts.The method proposed in this paper aims to integrate facial landmarks-driven representation into the triplet network.The spatial information provided by landmarks is introduced into the feature extraction process,so that the model can better capture the location relationship.In addition,coordinate information is also integrated into the triple loss calculation to further enhance similarity prediction.Specifically,for each image,the coordinates of 68 landmarks are detected,and then a region attention map based on these landmarks is generated.For the feature map output by the shallow convolutional layer,it will be multiplied with the attention map to correct the feature activation,so as to strengthen the key region and weaken the unimportant region.Finally,the optimized embedding output can be further used for downstream tasks.Three embeddings of three images output by the network can be regarded as a triplet representation for similarity computation.Through the CK+dataset,the effectiveness of such an optimized feature extraction is verified.After that,it is applied to facial expression similarity tasks.The results on the facial expression comparison(FEC)dataset show that the accuracy rate will be significantly improved after the landmark information is introduced.

Landmark在导航系统路径引导中的应用

通过对基于Landmark的路径引导的特点和相关研究方法进行分析,主要从定性的方向关系描述、Landmark与路径描述的整合以及Landmark的聚合3个方面讨论了Landmark被应用到车载导航系统的路径引导过程中的方法。从有效性、效率和满意度3个方面验证了基于Landmark的路径引导较传统的Turn-by-Turn式的路径引导更加符合人们的驾驶习惯,因此提高了导航的效率并降低了驾驶员的心理负荷。

AWI Signs Landmark Agreement with Leading Paris Style Agency

Australian Wool Innovation (AWI) today announced it had engaged world renowned style and innovation agency PeclersParis to provide colour and design trend direction for the Woolmark.Peclers’ team of fashion experts and trend forecasters this week

Landmark软件在华北油田钻井设计和施工中的应用

本文从井身结构优化、固井工艺设计、钻井液设计、完井设计等方面论述landmark软件在华北油田高难度井钻井设计的作用,以及现场施工中通过软件实时监测井眼轨迹的动向,确保井控安全和完钻井身质量。

A New Landmark for Exploration of the Cambrian Explosion

New studies suggest that the Kaili Biota in southwestern China's Guizhou Province could be the third revealing evidence for the spectacular Cambrian Explosion of life about 530 million years ago, next to the Burgess Shale Biota of Canada, found in 1909,and the Chengjiang Biota, brought to light in Yunnan Province, China,in 1984.

基于Landmark模型动态预测老年人轻度认知障碍向阿尔茨海默病的转化

目的利用Landmark模型对轻度认知障碍(mild cognitive impairment,MCI)的老年人转为阿尔茨海默病(Alzheimer′s disease,AD)的概率进行动态估计,为早期发现高危AD患者提供帮助。方法利用312名MCI个体的纵向和生存数据构建三个landmark模型(模型1、模型2和模型3)。利用Brier得分和C指数评估模型的预测性能并选出最优模型进行动态预测。结果模型3的预测性能较好,且FAQ、RAVLT-immediate和海马体体积是MCI转为AD重要的预测变量。在不同随访年,利用模型3和这三个预测变量预测两名MCI个体两年后转为AD的概率。MCI个体1转为AD的概率逐年下降,属于AD低危个体;而MCI个体2转为AD的概率逐年上升,属于AD高危个体。结论本研究对MCI个体向AD转化的概率进行动态估计,可识别AD高危群体。

基于Fortran编程提高LandMark软件地震解释层位精度和效率

在松辽盆地北部西部斜坡地区地震资料解释遇到大量地层超覆、地层尖灭情况。而利用LandMark解释软件进行岩性层位解释时必然会耗费大量的精力。利用Fortran语言编程对LandMark中的层位文件直接进行处理,提高了层位解释的精度与效率。

Accuracy and Repeatability of Computer Aided Cervical Vertebra Landmarking in Cephalogram

The accuracy and repeatability of computer aided cervical vertebra landmarking (CACVL) were investigated in cephalogram.120 adolescents (60 boys,60 girls) aged from 9.1 to 17.2 years old were randomly selected.Twenty-seven landmarks from the second to fifth cervical vertebrae on the lat-eral cephalogram were identified.In this study,the system of CACVL was developed and used to iden-tify and calculate the landmarks by fast marching method and parabolic curve fitting.The accuracy and repeatability in CACVL group were compared with those in two manual landmarking groups [orthodon-tic experts (OE) group and orthodontic novices (ON) group].The results showed that,as for the accu-racy,there was no significant difference between CACVL group and OE group no matter in x-axis or y-axis (P>0.05),but there was significant difference between CACVL group and ON group,as well as OE group and ON group in both axes (P<0.05).As for the repeatability,CACVL group was more reli-able than OE group and ON group in both axes.It is concluded that CACVL has the same or higher ac-curacy,better repeatability and less workload than manual landmarking methods.It’s reliable for cervi-cal parameters identification on the lateral cephalogram and cervical vertebral maturation prediction in orthodontic practice and research.

Endoscopic identification of endoluminal esophageal landmarks for radial and longitudinal orientation and lesion location

AIM To characterize esophageal endoluminal landmarks to permit radial and longitudinal esophageal orientation and accurate lesion location.METHODS Distance from the incisors and radial orientation were estimated for the main left bronchus and the left atrium landmarks in 207 consecutive patients using white light examination. A sub-study was also performed using white light followed by endoscopic ultrasound(EUS) in 25 consecutive patients to confirm the findings.The scope orientation throughout the exam was maintained at the natural axis,where the left esophageal quadrant corresponds to the area between 6 and 9 o'clock. When an anatomical landmark was identified, it was recorded with a photograph and its quadrant orientation and distance from the incisors were determined. The reference points to obtain the distances and radial orientation were as follows: the midpoint of the left main bronchus and the most intense pulsatile zone of the left atrium. With the video processor system set to moderate insufflation, measurements were obtained at the end of the patients' air expiration.RESULTS The left main bronchus and left atrium esophageal landmarks were identified using white light in 99% and 100% of subjects at a mean distance of 25.8 cm(SD2.3), and 31.4 cm(SD 2.4) from the incisors, respectively. The left main bronchus landmark was found to be a tubular, concave, non-pulsatile, esophageal external compression, occupying approximately 1/4 of the circumference. The left atrium landmark was identified as a round, convex, pulsatile, esophageal external compression, occupying approximately 1/4 of the circumference. Both landmarks were identified using white light on the anterior esophageal quadrant. In the substudy, the left main bronchus was identified in 24(92%) patients at 25.4 cm(SD2.1) and 26.7 cm(SD 1.9) from the incisors, by white light and EUS, respectively.The left atrium was recognized in all patients at 30.5 cm(SD 1.9), and 31.6 cm(SD2.3) from the incisors, by both white light and EUS, respectively. EUS confirmed that the landmarks corresponded to these two structures, respectively, and that they were located on the anterior esophageal wall. The Bland-Altman plot demonstrated high agreement between the white light and EUS measurements.CONCLUSION This study provides an endoscopic characterization of esophageal landmarks corresponding to the left main bronchus and left atrium, to permit radial and longitudinal orientation and accurate lesion location.

Localization of Mobile Robot Aided for Large-Scale Construction Based on Optimized Artificial Landmark Map in Ongoing Scene

The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization ability.Localization of mobile robot is increasingly important for the printing of buildings in the construction scene.Although many available studies on the localization have been conducted,only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless scenes.To realize the accurate localization of mobile robot in designated stations,we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of the whole map.Then,the performances of localization for mobile robot based on the original and optimized map are compared and evaluated.Finally,experimental results show that the average absolute localization errors that adopted the proposed algorithm is reduced by about 21%compared to that of the original map.

Universal precursor seismicity pattern before locked-segment rupture and evolutionary rule for landmark earthquakes

Despite extensive investigations,no precursor patterns for reliably predicting major earthquakes have thus far been identified.Seismogenic locked segments that can accumulate adequate strain energy to cause major earthquakes are highly heterogeneous and low brittle.The progressive cracking of the locked segments with these properties can produce an interesting seismic phenomenon:a landmark earthquake and a sequence of smaller subsequent earthquakes(pre-shocks)always arise prior to another landmark earthquake within a well-defined seismic zone and its current seismic period.Applying a mechanical model,magnitude constraint conditions,and case study data of 62 worldwide seismic zones,we show that two adjacent landmark earthquakes reliably occur at the volume-expansion point and peak-stress point(rupture)of a locked segment;thus,the former is an identified precursor for the latter.Such a precursor seismicity pattern before the locked-segment rupture has definite physical meanings,and it is universal regardless of the focal depth.Because the evolution of landmark earthquakes follows a deterministic rule described by the model,they are predictable.The results of this study lay a firm physical foundation for reliably predicting the occurrence of future landmark earthquakes in a seismic zone and can greatly improve our understanding of earthquake generation mechanism.

Street-Level IP Geolocation Algorithm Based on Landmarks Clustering

Existing IP geolocation algorithms based on delay similarity often rely on the principle that geographically adjacent IPs have similar delays.However,this principle is often invalid in real Internet environment,which leads to unreliable geolocation results.To improve the accuracy and reliability of locating IP in real Internet,a street-level IP geolocation algorithm based on landmarks clustering is proposed.Firstly,we use the probes to measure the known landmarks to obtain their delay vectors,and cluster landmarks using them.Secondly,the landmarks are clustered again by their latitude and longitude,and the intersection of these two clustering results is taken to form training sets.Thirdly,we train multiple neural networks to get the mapping relationship between delay and location in each training set.Finally,we determine one of the neural networks for the target by the delay similarity and relative hop counts,and then geolocate the target by this network.As it brings together the delay and geographical coordinates clustering,the proposed algorithm largely improves the inconsistency between them and enhances the mapping relationship between them.We evaluate the algorithm by a series of experiments in Hong Kong,Shanghai,Zhengzhou and New York.The experimental results show that the proposed algorithm achieves street-level IP geolocation,and comparing with existing typical streetlevel geolocation algorithms,the proposed algorithm improves the geolocation reliability significantly.

LandMark系统在煤田地震勘探解释成图中的应用

应用LandMark系统可极大地提高地震资料解释成图的速度,减轻数据整理及图件绘制的工作量。结合实例简要介绍了应用LandMark系统进行煤田地震勘探资料解释及成图的具体方法,并对LandMark系统成图与以往成图方法进行了比较。

Landmark和Geoframe软件的集成

Landmark和Geoframe软件所带数据库不能同时存在于同一硬件上,所以只能将其安装在不同的工作站上,这样增加了硬件成本,又给实际工作带来问题。利用Oracle数据库多实例共存的特点,解决同一硬件系统上数据库共存的问题,实现Landmark和Geoframe软件的集成。通过实际工作的检验,集成的软件运行稳定正常,用户使用方便,软件集成技术操作简单、实用。

Landmark钻井软件在陆丰油田调整井中的应用

Landmark钻井软件Compass模块和Wellplan模块可以对井眼轨迹进行优化设计,模拟钻井过程中不同工况下的水力摩阻等,在海上钻井施工中有广泛的应用。本文分析了陆丰油田22H1井的侧钻方式、井眼水力摩阻的模拟及最小携岩排量的确定。软件模拟结果表明:22H1井最佳侧钻方式是从老井22井1600米处开窗侧钻,此时平台设备满足钻井水力摩阻扭矩要求,同时在稳斜段的最小携岩排量是2150L/min。

LandMark系统综合应用的初步开发

LandMark系统在地勘行业的应用日益广泛，涉及到各个不同的学科，我们比较熟悉地震解释模块，在使用多个模块进行综合解释方面尚不够成熟，综合应用能极大的提高效率及数据的完整性．本文旨在抛砖引玉，将这一系统的应用推向一个新的高度．

基于Landmark的声纹识别技术在电影放映监测中的探索实验

目前在高速发展的电影市场下,偷漏瞒报票房、影片盗录盗放等乱象屡屡出现,严重扰乱了电影市场秩序,因此加强影厅放映内容的监管需求也更为迫切.本文在此背景上将声纹识别技术在电影放映领域进行探索实验,通过在影片播放过程中采集声音样本,并根据Landmark算法构造声纹特征进行匹配,最终达到识别放映内容的结果,为影院放映监测机制提供有效思路.本实验已基本实现该功能并具有较高识别率,但在后期仍需在算法优化改进中做进一步探索.

LandMark导入数据格式转换软件的实现

LandMark地震资料解释系统在基础数据的导入操作中,存在数据格式要求严格、数据量大和数据种类多的问题,为数据准备工作带来麻烦。为解决该问题,笔者开发的面向LandMark导入数据格式转换软件实现了LandMark常用导入数据文件的规格化快速转换。该软件的应用表明,LandMark导入数据准备过程工作效率比之前提高了5倍以上,导入数据准确率也有了极大的提高。