透视视觉文化批判——《视觉批判导论》作者吴琼访谈

《视觉批判导论》一书从视觉文化研究的批判性视角出发,梳理了视觉文化研究的谱系、对象、基本框架和主要论题,深入探讨了视觉性在视觉实践中的运作机制。该书不仅反思了视觉中心主义及其在现代社会中的影响,还研究了视觉机器如何作为社会控制工具,以及观看行为背后的权力运作和主体建构。通过批判性分析,揭示视觉文化在当代社会中的复杂面貌及其背后的意识形态。

高校《视觉传达设计》产教结合的工作室制教学模式研究

伴随着市场经济体系的革新,高校教学工作产生了新的变化,针对于高效《视觉传达设计》专业构建产教结合工作室制教学模式遵循了应用型人才培养的目标和要求,通过实践性教学为学生提供了实践探索的场所及通道,借此培养了学生的操作技能,丰富了学生的经验和经历。本文探索高效《视觉传达设计》产教结合的工作室制教学模式,希望能为这种教学模式的有效应用提供参考。

感官与心灵:中西方的不同命运——从鲁道夫·阿恩海姆《视觉思维——审美直觉心理学》谈起

《视觉思维》不是一个偶然诞生的奇迹 ,西哲在重视抽象思维的同时 ,并不忽视感官的作用 ;重视感知在思维过程中的作用 ,从不省略直观、实证的求知过程 ,是西方哲学一以贯之的传统。反观中国古代哲学 ,总是忽略、轻视甚至排斥感官的作用 ,而倾向直接以心灵去把握真理 ;而这种“心灵”,又是经过伦理精心过滤的 ,无所不能。其结果是 ,在古代思想家笔下 ,存在着两组既互为独立又相互渗透的思想现象 :一、圣化心灵与圣化王权同步 ,二者之间存在着一种同向互动关系 ;二、圣化心灵与奴化感官同步 。

图像视觉意义的构建——评《视觉方法论》第四版

视觉传播以其无以伦比的直观性,在多媒体多模态的现代传播模式中占据越来越重要的地位。概括Gillian Rose从视觉文化理论基础上的最新力作:第四版《视觉方法论》,梳理出其与前三版的修订之处,介绍基于四个场域和三个模块基础上的图像分析理论框架,采用社会符号学的方法着重探讨图像视觉意义的构建。

被视觉机器超越的人类知觉——评析保罗·维利里奥的《视觉机器》

保罗·维利里奥在《视觉机器》一书中通过西方艺术实践史展现了光线如何因速度而变化,进而人类知觉实践随之发生的变化及后果。时-空是他考察速度对人类艺术实践造成后果的着眼点:现代视觉技术与艺术凝固了时间,造成人类空间失忆,从而引发人类知觉体系的断裂与崩坏。

关乎视觉 更关乎历史——评《视觉传达设计史》

随着人类科技的发展,社会对视觉传达设计的要求越来越高,视觉传达设计对社会的独特作用也越来越受到人们的重视。如今各大高校的视觉传达设计专业在专业教学中对白石和也先生所著的《视觉传达设计史》一书的重视程度也越来越高。每门真正拥有成熟体系的学科中都有史论研究,以记录这门学科的起源、发展辉煌、没落、崛起,及对未来的畅想。随着视觉传达艺术的传播范围越来越广,人们对其发展历史的研究逐渐深入。

视觉的冲击

在网上和朋友聊天时喜欢以图为证，口头弹就是“有图有真相”。对我而言，图片的视觉冲击力远非文字所能比拟。在连续看了贵刊几期的《视觉》栏目后，感觉更是如此。

标志设计的图形元素应用分析——以《视觉传达艺术设计》教学为例

本文以《视觉传达艺术设计》一课教学为例,论述标志设计的图形元素运用策略,分析其在内涵性、指向性、美观性及关联性等方面的应用,培养学生的观察能力、想象能力和创新创造能力。

视觉手记

下午，我走着去位于上海老洋房区的工作室，阳光很好．是那种让人容易浮想联翩的阳光。

高等教育自学考试《服装艺术设计》专业（专、本科）《视觉传达设计》专业（专科）等三个专业的部分课程考试办法有改变

为适应社会经济发展的需要，加强应试者的动手操作能力培养，满足日益发展的服装行业对服装设计人才的需求，应主考院校和委托单位要求，决定调整高等教育自学考试《服装艺术设计》专业（专科）、《服装艺术设计》专业（独立本科段）、《视觉传达设计》专业（专科）等三个专业的部分课程考试办法。调整后的课程计划自2007年4月开始执行，原计划废止，老考生考过的课程成绩相应顶替新计划中的课程成绩。调整后的专业课程考试计划如下：

罗杰·弗莱的中国古典艺术研究及其形式美学建构

本文拟在回顾英国艺术评论家罗杰·弗莱的美学探索之路及与中国艺术渊源的基础上,探讨其中国古典艺术研究的成就与特色,认为弗莱以形式分析为门径,以《伯灵顿杂志》等为阵地,成功地将中国艺术精神融入了形式美学话语之中,由此助推了西方现代主义艺术运动的发展。作为现代主义全球流动的一个典型个案,弗莱与中国艺术的亲缘关系十分有力地证明了中国古典艺术美学在全球现代主义发展中的独特作用。

Wafer Defect Map Pattern Recognition Based on Improved ResNet

The defect detection of wafers is an important part of semiconductor manufacturing.The wafer defect map formed from the defects can be used to trace back the problems in the production process and make improvements in the yield of wafer manufacturing.Therefore,for the pattern recognition of wafer defects,this paper uses an improved ResNet convolutional neural network for automatic pattern recognition of seven common wafer defects.On the basis of the original ResNet,the squeeze-and-excitation(SE)attention mechanism is embedded into the network,through which the feature extraction ability of the network can be improved,key features can be found,and useless features can be suppressed.In addition,the residual structure is improved,and the depth separable convolution is added to replace the traditional convolution to reduce the computational and parametric quantities of the network.In addition,the network structure is improved and the activation function is changed.Comprehensive experiments show that the precision of the improved ResNet in this paper reaches 98.5%,while the number of parameters is greatly reduced compared with the original model,and has well results compared with the common convolutional neural network.Comprehensively,the method in this paper can be very good for pattern recognition of common wafer defect types,and has certain application value.

Development status and prospect of cold chain logistics of fruits,vegetables,and agricultural products based on intelligent technology

The cold chain in the production area of fruits and vegetables is the primary link to reduce product loss and improve product quality,but it is also a weak link.With the application of big data technology in cold chain logistics,intelligent devices,and technologies have become important carriers for improving the efficiency of cold chain logistics in fruit and vegetable production areas,extending the shelf life of fruits and vegetables,and reducing fruit and vegetable losses.They have many advantages in fruit and vegetable pre-cooling,sorting and packaging,testing,warehousing,transportation,and other aspects.This article summarizes the rapidly developing and widely used intelligent technologies at home and abroad in recent years,including automated guided vehicle intelligent handling based on electromagnetic or optical technology,intelligent sorting based on sensors,electronic optics,and other technologies,intelligent detection based on computer vision technology,intelligent transportation based on perspective imaging technology,etc.It analyses and studies the innovative research and achievements of various scholars in applying intelligent technology in fruit and vegetable cold chain storage,sorting,detection,transportation,and other links,and improves the efficiency of fruit and vegetable cold chain logistics.However,applying intelligent technology in fruit and vegetable cold chain logistics also faces many problems.The challenges of high cost,difficulty in technological integration,and talent shortages have limited the development of intelligent technology in the field of fruit and vegetable cold chains.To solve the current problems,it is proposed that costs be controlled through independent research and development,technological innovation,and other means to lower the entry threshold for small enterprises.Strengthen integrating intelligent technology and cold chain logistics systems to improve data security and system compatibility.At the same time,the government should introduce relevant policies,provide necessary financial support,and establish talent training mechanisms.Accelerate the development and improvement of intelligent technology standards in the field of cold chain logistics.Through technological innovation,cost control,talent cultivation,and policy guidance,we aim to promote the upgrading of the agricultural industry and provide ideas for improving the quality and efficiency of fruit and vegetable cold chain logistics.

Visual navigation in orchard based on multiple images at different shooting angles

The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve autonomous navigation in orchard,a visual navigation method based on multiple images at different shooting angles is proposed in this paper.A dynamic image capturing device is designed for camera installation and multiple images can be shot at different angles.Firstly,the obtained orchard images are classified into sky and soil detection stage.Each image is transformed to HSV space and initially segmented into sky,canopy and soil regions by median filtering and morphological processing.Secondly,the sky and soil regions are extracted by the maximum connected region algorithm,and the region edges are detected and filtered by the Canny operator.Thirdly,the navigation line in the current frame is extracted by fitting the region coordinate points.Then the dynamic weighted filtering algorithm is used to extract the navigation line for the soil and sky detection stage,respectively,and the navigation line for the sky detection stage is mirrored to the soil region.Finally,the Kalman filter algorithm is used to fuse and extract the final navigation path.The test results on 200 images show that the accuracy of visual navigation path fitting is 95.5%,and single frame image processing costs 60 ms,which meets the real-time and robustness requirements of navigation.The visual navigation experiments in Camellia oleifera orchard show that when the driving speed is 0.6 m/s,the maximum tracking offset of visual navigation in weed-free and weedy environments is 0.14 m and 0.24 m,respectively,and the RMSE is 30 mm and 55 mm,respectively.

Contrast Detection Learning Improves Visual Contrast Sensitivity of Cat

Psychological studies on human subjects show that contrast detection learning promote learner＇s sensitivity to visual stimulus contrast. The underlying neural mechanisms remain unknown. In this study, three cats （Felis catus） were trained to perform monocularly a contrast detection task by two-altemative forced choice method. The perceptual ability of each cat improved remarkably with learning as indicated by a significantly increased contrast sensitivity to visual stimuli. The learning effect displayed an evident specificity to the eye employed for learning but could partially transfer to the naive eye, prompting the possibility that contrast detection learning might cause neural plasticity before and after the information from both eyes are merged in the visual pathway. Further, the contrast sensitivity improvement was evident basically around the spatial frequency （SF） used for learning, which suggested that contrast detection learning effect showed, to some extent, a SF specificity. This study indicates that cat exhibits a property of contrast detection learning similar to human subjects and can be used as an animal model for subsequent investigations on the neural correlates that mediate learning-induced contrast sensitivity improvement in humans.

Visual modeling reveals cryptic aspect in egg mimicry of Himalayan Cuckoo(Cuculus saturatus) on its host Blyth's Leaf Warbler(Phylloscopus reguloides)

Brood parasitism and egg mimicry of Himalayan Cuckoo（Cuculus saturatus） on its host Blyth＇s Leaf Warbler（Phylloscopus reguloides） were studied in south-western China from April to July 2009.The cuckoo laid a white egg with fine brown markings on the blunt end.The eggs were conspicuously bigger than the host＇s own,with 2.06 g in mass and 1.91 cm3 in volume.Visual modeling showed that the cuckoo eggs,which from the human eye appeared to mimic the host eggs to a great extent,were completely different from the host eggs in both hue and chroma.The characters of the Himalayan Cuckoo nestling,reported for the first time,included two triangular and black patches on its gape,which appeared from four days old and became darker with age and growth.While this character also exists in nestlings of Oriental Cuckoo（C.optatus）,it has not been found for other Cuculus species.Our results reveal cryptic aspects in the cuckoo-host egg color matching,which are not visible to the naked human eye,and indicate that high mimetic cuckoo eggs rejected by hosts,as determined by human observers in previous studies,might not be mimetic as birds see them.

High-precision automatic measurement of two-dimensional geometric features based on machine vision

To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view （FOV） images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0. 03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.

Research on detection of lane based on machine vision

To prevent a vehicle from departing the lane in assistant or automatic steering, real-time vision-based detection of lane is studied. The system architecture, detecting principle and lane model are described. Then the detecting algorithm of the lane image is discussed in detail. In this algorithm, several proper sub-windows in one image are first selected as the processing regions. To every sub-window, by means of such steps as appropriate pre-processing, edge detection and Hough transform, etc., the lane description features are extracted. Experimental results reveal that this detection method is of good real-time, high recognition reliability and strong robustness, etc., which can provide the decision-making foundation for the following automatic or assistant steering to some extent.