A Concise and Varied Visual Features-Based Image Captioning Model with Visual Selection

Image captioning has gained increasing attention in recent years.Visual characteristics found in input images play a crucial role in generating high-quality captions.Prior studies have used visual attention mechanisms to dynamically focus on localized regions of the input image,improving the effectiveness of identifying relevant image regions at each step of caption generation.However,providing image captioning models with the capability of selecting the most relevant visual features from the input image and attending to them can significantly improve the utilization of these features.Consequently,this leads to enhanced captioning network performance.In light of this,we present an image captioning framework that efficiently exploits the extracted representations of the image.Our framework comprises three key components:the Visual Feature Detector module(VFD),the Visual Feature Visual Attention module(VFVA),and the language model.The VFD module is responsible for detecting a subset of the most pertinent features from the local visual features,creating an updated visual features matrix.Subsequently,the VFVA directs its attention to the visual features matrix generated by the VFD,resulting in an updated context vector employed by the language model to generate an informative description.Integrating the VFD and VFVA modules introduces an additional layer of processing for the visual features,thereby contributing to enhancing the image captioning model’s performance.Using the MS-COCO dataset,our experiments show that the proposed framework competes well with state-of-the-art methods,effectively leveraging visual representations to improve performance.The implementation code can be found here:https://github.com/althobhani/VFDICM(accessed on 30 July 2024).

Effect of capsule treatment on visual acuity and quality after phacoemulsification lens implantation in myopic patients with cataract

BACKGROUND Cataracts pose a significant clinical burden due to their complex pathogenesis.In recent years,an increase in cataracts coexisting with myopia has heightened the incidence of retinopathy and posterior vitreous detachment.Additionally,symptoms of ocular axis elongation,lens nucleus hardening,and vitreous liquefaction have become more prevalent.While conventional extracapsular cataract extraction is commonly employed,it often yields suboptimal visual outcomes.Subsequent advancements in cataract phacoemulsification and lens implantation surgeries have gained widespread acceptance for their ability to improve refraction and significantly improve uncorrected visual acuity.AIM To investigate the effect of capsular treatment after phacoemulsification lens implantation in myopic patients with cataract.METHODS We selected 110 patients(with 134 eyes)with myopia and cataracts treated.These patients were categorized into two groups:an observation group(57 patients with 70 eyes)and a control group(53 patients with 64 eyes).The control group underwent cataract phacoemulsification and lens implantation,while the observation group received a refined capsular treatment based on the control group’s procedure.We assessed the differences in visual acuity and quality between the two groups before and after surgery.RESULTS At six months post-operation,the observation group exhibited significantly improved far vision,intermediate vision,near vision,lower objective scattering index,higher Modulation transfer function cut-off frequency,and overall vision metrics at different contrast levels(100%,20%and 9%)compared to the control group(P<0.05).The total score of the National Eye Institute Visual Function Questionnaire in the observation group at 6 months after operation was significantly higher than that in the control group(P<0.05).No significant difference in the incidence of adverse reactions was observed between the observation group and control group(P>0.05).CONCLUSION Capsular treatment demonstrates efficacy in improving visual acuity and quality after phacoemulsification lens implantation in myopic patients with cataracts,warranting its clinical application.

Application of Landscape Engineering based on BIM Visualization Technology

The rapid advancement of building information modeling(BIM)technology has garnered significant interest regarding its application within the domain of landscape engineering.BIM technology,as a construction and management tool that integrates digitization and visualization,has demonstrated considerable advantages in enhancing project quality,reducing costs,and improving collaborative efficiency.This study aims to systematically investigate the application and developmental trends of BIM visualization technology within the field of landscape engineering.Through an analysis of technological advancements and industry dynamics over the past decade,it has been observed that BIM visualization technology is intricately linked with green building practices,sustainable construction methods,and the development of smart cities within the context of landscape engineering projects.The technology also possesses significant potential for application in the planning and design of landscape engineering,construction management,and project maintenance.The convenience of visualization enhances the expressive capacity of the design scheme,improves communication efficiency between the involved parties,and mitigates the costs and time inefficiencies associated with design modifications.By drawing on the successful experiences of other industries and integrating them with the unique characteristics of landscape engineering,BIM visualization technology is poised to assume a more significant role within this field.This integration is expected to advance the entire industry towards greater intelligence and informatization,while simultaneously enhancing the efficiency and quality of design,construction,and maintenance processes.

Visual Representation and Cognitive Models in Information Visualization

As a branch of computer science,information visualization aims to help users understand and analyze complex data through graphical interfaces and interactive technologies.Information visualization primarily includes various visual structures such as time-series structures,spatial relationship structures,statistical distribution structures,and geographic map structures,each with unique functions and application scenarios.To better explain the cognitive process of visualization,researchers have proposed various cognitive models based on interaction mechanisms,visual perception steps,and novice use of visualization.These models help understand user cognition in information visualization,enhancing the effectiveness of data analysis and decision-making.

集成PHAST-Visual Studio的岩溶区燃气管道灾害后果定量分析及应用

为科学评估岩溶区燃气管道灾害的后果影响程度,基于管道失效特征确定喷射火和蒸气云爆炸两种典型后果模式,研判适用于岩溶区燃气管道灾害的热辐射和冲击波超压危害准则,从危害面积、伤亡人数、经济损失、环境破坏4个维度提出岩溶区燃气管道灾害后果严重程度的评估模型体系,并结合Visual Studio平台开发“岩溶区燃气管道灾害后果分析软件”。立足岩溶区实际工程案例,结合区域经济社会发展、岩溶自然地质以及燃气管道工程特征,基于PHAST软件仿真分析灾害后果的影响范围,结合危害准则对区内人员、物体提出针对性灾害风险管控措施,并通过引入政府、行业、企业等颁布的标准条例,量化得出灾害后果的影响程度。结果表明:提出的PHAST-Visual Studio集成方法能够弥补以往研究的评估主观性问题,将社会科学思想带入工程风险评价研究,并通过计算机软件编程提高灾害后果分析效率,从而有助于显著控制岩溶区燃气管道灾害后果水平。

Visual Semantic Segmentation Based on Few/Zero-Shot Learning:An Overview

Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block,and it plays a crucial role in environmental perception.Conventional learning-based visual semantic segmentation approaches count heavily on largescale training data with dense annotations and consistently fail to estimate accurate semantic labels for unseen categories.This obstruction spurs a craze for studying visual semantic segmentation with the assistance of few/zero-shot learning.The emergence and rapid progress of few/zero-shot visual semantic segmentation make it possible to learn unseen categories from a few labeled or even zero-labeled samples,which advances the extension to practical applications.Therefore,this paper focuses on the recently published few/zero-shot visual semantic segmentation methods varying from 2D to 3D space and explores the commonalities and discrepancies of technical settlements under different segmentation circumstances.Specifically,the preliminaries on few/zeroshot visual semantic segmentation,including the problem definitions,typical datasets,and technical remedies,are briefly reviewed and discussed.Moreover,three typical instantiations are involved to uncover the interactions of few/zero-shot learning with visual semantic segmentation,including image semantic segmentation,video object segmentation,and 3D segmentation.Finally,the future challenges of few/zero-shot visual semantic segmentation are discussed.

Visual Modflow在和田县农业经济新区地下水资源评价中的应用

为全面了解地下水系统受各种激励因素影响后的水动力场和地下水量变化规律,以及为当地地下水资源开发与利用提供科学的指导意见,本次在和田县农业经济新区地下水资源评价中采用可视化标准软件Visnal Modflow实现地下水资源的模拟与预报,通过构建三维非稳定流数值模型,使用迭代方法求解,并根据设计开采量对地下水水位变动做出预测,再基于建模预测结果,结合经济新区地下水资源量确定合理的地下水开采量。

基于Visual MODFLOW大水矿山深部开采矿坑涌水量预测

矿产资源的不断开发导致矿坑涌、突水现象愈加频繁,此类问题多发生于大水矿山,为更好指导大水矿山深部开采工作,准确预测矿山深部开采矿坑涌水量至关重要。结合某矿区勘察资料、水文地质条件和观测井实测水位数据,利用Visual MODFLOW软件建立矿区水文地质数值模型,进行稳态与非稳态校正以及相关参数敏感性分析;根据该矿区-150 m水平矿坑真实涌水量拟合分析Drain模块水力传导系数值,运用识别后模型对矿山深部开采矿坑涌水量预测,结果表明-200、-250、-300、-350 m等不同水平矿坑正常涌水量为17209.82、18896.20、21299.31、23494.10 m^(3)/d,预测结果可为矿山防治水工作提供依据,以及为工程安全开挖提供保障。

Heterogeneous Image Knowledge Driven Visual Perception

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous images.Facing the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

Prevalence of visual impairment and estimation of refractive errors among school children in Kakamega,Kenya

AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.

Morphological disruption and visual tuning alterations in the primary visual cortex in glaucoma(DBA/2J)mice

Glaucoma is a leading cause of irreve rsible blindness wo rldwide,and previous studies have shown that,in addition to affecting the eyes,it also causes abnormalities in the brain.However,it is not yet clear how the primary visual cortex(V1)is altered in glaucoma.This study used DBA/2J mice as a model for spontaneous secondary glaucoma.The aim of the study was to compare the electrophysiological and histomorphological chara cteristics of neurons in the V1between 9-month-old DBA/2J mice and age-matched C57BL/6J mice.We conducted single-unit recordings in the V1 of light-anesthetized mice to measure the visually induced responses,including single-unit spiking and gamma band oscillations.The morphology of layerⅡ/Ⅲneurons was determined by neuronal nuclear antigen staining and Nissl staining of brain tissue sections.Eighty-seven neurons from eight DBA/2J mice and eighty-one neurons from eight C57BL/6J mice were examined.Compared with the C57BL/6J group,V1 neurons in the DBA/2J group exhibited weaker visual tuning and impaired spatial summation.Moreove r,fewer neuro ns were observed in the V1 of DBA/2J mice compared with C57BL/6J mice.These findings suggest that DBA/2J mice have fewer neurons in the VI compared with C57BL/6J mice,and that these neurons have impaired visual tuning.Our findings provide a better understanding of the pathological changes that occur in V1 neuron function and morphology in the DBA/2J mouse model.This study might offer some innovative perspectives regarding the treatment of glaucoma.

Recent progress in visualization and digitization of coherent transformation structures and application in high-strength steel

High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of dislocations and fine crystallographic structural units,which ease the coordinated matching of high strength,toughness,and plasticity.Meanwhile,given its excellent welding perform-ance,high-strength steel has been widely used in major engineering constructions,such as pipelines,ships,and bridges.However,visual-ization and digitization of the effective units of these coherent transformation structures using traditional methods(optical microscopy and scanning electron microscopy)is difficult due to their complex morphology.Moreover,the establishment of quantitative relationships with macroscopic mechanical properties and key process parameters presents additional difficulty.This article reviews the latest progress in microstructural visualization and digitization of high-strength steel,with a focus on the application of crystallographic methods in the development of high-strength steel plates and welding.We obtained the crystallographic data(Euler angle)of the transformed microstruc-tures through electron back-scattering diffraction and combined them with the calculation of inverse transformation from bainite or martensite to austenite to determine the reconstruction of high-temperature parent austenite and orientation relationship(OR)during con-tinuous cooling transformation.Furthermore,visualization of crystallographic packets,blocks,and variants based on actual OR and digit-ization of various grain boundaries can be effectively completed to establish quantitative relationships with alloy composition and key process parameters,thereby providing reverse design guidance for the development of high-strength steel.

基于Visual Modflow的拉萨贡嘎机场跑道地下水模拟

机场作为综合运输体系的重要设施,在“十四五”期间,中国民用机场发展已经进入规划建设高峰期。拉萨贡嘎机场拟建跑道位于河漫滩,场区附近辫状河道发育,有地下水位高、地层岩性渗透性强等问题。文章就拟建跑道在常水位工况和百年一遇工况渗流场变化情况及场区渗透变形分析展开了研究,为后续工程建设提供相应参考依据。

RMPC-Based Visual Servoing for Trajectory Tracking of Quadrotor UAVs With Visibility Constraints

Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.

Women in visual neural regeneration research

The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to examine the state of gender bias in a relatively new yet already prominent field,neural regeneration in the visual system,for which there is a well-defined context useful for this purpose.The National Eye Institute(NEI)provided the first round of research funding for its Audacious Goals Initiative(AGI)on visual neural regeneration in 2013 and the last round in 2021.Therefore,we focus on this timespan.Data sources included PubMed,the National Science Foundation(NSF),the NEI,the Blue Ridge Institute for Medical Research and data from the major professional organization for eye and vision research,the Association for Research in Vision and Ophthalmology(ARVO).

Bioactive material promotes longdistance regeneration of optic nerve to restore visual functions

Visual system is vital to human beings.Unfortunately,the optic nerve lacks the ability to regenerate after injury.Therefo re,long-distance regeneration of the optic nerve is a major unsolved medical problem in the world(Laha et al.,2017).Recently,Li and So groups' study showed that the bioactive material(ciliary neurotrophic factor[CNTF]-chitosan) could promote long-distance regeneration of the completely transected optic nerve in adult rats and partially restored the visual functions(Liu et al.,2023).This study sheds light on the clinical potential for repairing the severely injured optic nerve.

SMSTracker:A Self-Calibration Multi-Head Self-Attention Transformer for Visual Object Tracking

Visual object tracking plays a crucial role in computer vision.In recent years,researchers have proposed various methods to achieve high-performance object tracking.Among these,methods based on Transformers have become a research hotspot due to their ability to globally model and contextualize information.However,current Transformer-based object tracking methods still face challenges such as low tracking accuracy and the presence of redundant feature information.In this paper,we introduce self-calibration multi-head self-attention Transformer(SMSTracker)as a solution to these challenges.It employs a hybrid tensor decomposition self-organizing multihead self-attention transformermechanism,which not only compresses and accelerates Transformer operations but also significantly reduces redundant data,thereby enhancing the accuracy and efficiency of tracking.Additionally,we introduce a self-calibration attention fusion block to resolve common issues of attention ambiguities and inconsistencies found in traditional trackingmethods,ensuring the stability and reliability of tracking performance across various scenarios.By integrating a hybrid tensor decomposition approach with a self-organizingmulti-head self-attentive transformer mechanism,SMSTracker enhances the efficiency and accuracy of the tracking process.Experimental results show that SMSTracker achieves competitive performance in visual object tracking,promising more robust and efficient tracking systems,demonstrating its potential to providemore robust and efficient tracking solutions in real-world applications.

Fluorescent Double Network Hydrogels with Ionic Responsiveness and High Mechanical Properties for Visual Detection

We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.

Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes

●AIM:To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes.●METHODS:Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited.Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients’medical records.A hierarchical cluster analysis was performed.The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts.●RESULTS:A total of 164 children(299 eyes)were divided into two clusters based on their ocular features.Cluster 1(96 eyes)had a shorter axial length(mean±SD,19.44±1.68 mm),a low prevalence of macular abnormalities(1.04%),and no retinal abnormalities or posterior cataracts.Cluster 2(203 eyes)had a greater axial length(mean±SD,20.42±2.10 mm)and a higher prevalence of macular abnormalities(8.37%),retinal abnormalities(98.52%),and posterior cataracts(4.93%).Compared with the eyes in Cluster 2(57.14%),those in Cluster 1(71.88%)had a 2.2 times higher chance of good best-corrected visual acuity[<0.7 logMAR;OR(95%CI),2.20(1.25–3.81);P=0.006].●CONCLUSION:This retrospective study categorizes congenital cataracts into two distinct clusters,each associated with a different likelihood of visual outcomes.This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit,thereby making strides toward precision medicine in the field of congenital cataracts.

Enhancing visual security: An image encryption scheme based on parallel compressive sensing and edge detection embedding

A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete wavelet transform.Then, the coefficient matrix is scrambled and compressed to obtain a size-reduced image using the Fisher–Yates shuffle and parallel compressive sensing. Subsequently, to increase the security of the proposed algorithm, the compressed image is re-encrypted through permutation and diffusion to obtain a noise-like secret image. Finally, an adaptive embedding method based on edge detection for different carrier images is proposed to generate a visually meaningful cipher image. To improve the plaintext sensitivity of the algorithm, the counter mode is combined with the hash function to generate keys for chaotic systems. Additionally, an effective permutation method is designed to scramble the pixels of the compressed image in the re-encryption stage. The simulation results and analyses demonstrate that the proposed algorithm performs well in terms of visual security and decryption quality.