我们衷心感谢武汉城建集团2023年度科研专项（NO.7）对这项工作的资助。

1.具体样品图像采集
<ol><li>将混凝土运输到工作场所，由泵车浇筑。</li>
	<li>要拍摄图像，请通过向右移动电源键开关并将其转到 ON 位置来打开拍摄设备。将相机的模式旋钮调整到绿色自动模式，确保相机镜头与混凝土表面平行，然后按 下快门键。捕获 20 个非振动混凝土的图像样本，将它们保存为采集分辨率为 1024 x 1024 像素的.jpg格式，如 图 1 所示。</li>
	<li>将混凝土振动设备的振动部分（插入式混凝土振动杆）插入混凝土中。连接电源，然后通过将其设置为 ON 位置来打开混凝土振动设备。</li>
	<li>当混凝土表面出现一些坍塌（由混凝土内部释放空气的振动引起，导致表面骨料下沉以填充缝隙，导致混凝土坍塌）并出现一些水泥浆时，保持相机镜头平行于混凝土表面并按 下快门键。收集 20 个振动混凝土的图像样本，如 图 2 所示。</li>
	<li>继续操作振动设备。当混凝土表面无明显塌陷时，不出现水泥浆，不产生气泡，停止振动过程，采集20张振动混凝土图像样本，如 图3所示。</li>
</ol>2. 样本图像灰度二值化
<ol><li>利用 MATLAB 软件的 imread（） 函数将 .jpg 文件读取为 1024 像素 x 1024 像素 x 3 个颜色通道的单位格式数据，表示图像的红色、绿色和蓝色通道值。</li>
	<li>接下来，应用 MATLAB 函数 rgb2gray 将图像转换为灰度，用格式 gray value = rgb2gray（jpg file name） 表示。根据公式（1）计算每个像素的灰度值，并将灰度值保存为1024 x 1024的unit8格式数据。 GR（i，j） = 0.2989R（i，j） + 0.587G（i，j） + 0.114B（i，j） （1） 其中，GR（i，j） 是像素点的灰度值，R（i，j） 是像素点的红色通道值，G（i，j） 是像素点的绿色通道值，B（i，j） 是像素点的蓝色通道值。</li>
	<li>将大于像素阈值 θ 的灰度值的二进制值更改为 1，并将小于 θ 像素的灰度值的二进制值设置为 0。</li>
	<li>获得二值灰度结果后，将结果另存为 1024 x 1024 逻辑格式数据。在本例中，θ 表示二值化阈值，对于不同振动状态的混凝土样品图像，其值分别为 50、100、150 和 200，如 图 5、 图 6 和 图 7 所示。</li>
</ol>3. 定向梯度特征值的计算
<ol><li>使用以下公式28 计算图像中每个像素的水平和垂直二进制梯度 Tp = R（x， y + 1） - R（x， y - 1）， Th = R（x+1， y） - R（x-1， y） 其中 Th 是水平二值化梯度，Tp 是垂直二值化梯度，R 是二值化逻辑格式数据，x 是二值化矩阵的行号，y 是二值化矩阵的列号。</li>
	<li>使用以下公式29 计算每个点的二进制梯度方向和大小 <img alt="Equation 1" src="/files/ftp_upload/65731/65371eq01.jpg" style="margin: auto;"> 其中 T 是二进制梯度大小，αT 是二进制梯度方向，Th 是水平二进制梯度，Tp 是垂直二进制梯度。</li>
	<li>确定图像分割块的大小，表示为 n，其中 n 的值为 [ 1,9]。沿 x 方向在 y 方向上设置每个 n 像素的分割线，根据分割线的位置有效地将图像分成 n x n 个正方形块。然后，图像中无法形成完整方形块的任何部分都将被删除。</li>
	<li>将T α二进制梯度方向（T α二进制梯度方向的值为 [ 0°， 360°]）划分为 m 个部分，得到 m 个方向梯度统计角度区间。继续计算每个块的梯度统计角度间隔的梯度统计值。<ol><li>根据块中每个像素的二进制梯度方向，将像素分类为每个方向的适当梯度统计角度区间。</li>
		<li>将每个方向的梯度统计角度间隔内像素在逆时针方向上的二进制梯度求和，得到该间隔的梯度统计值。 图 8、 图 9 和 图 10 分别描绘了块大小 n 等于 8、128 和 512 的梯度统计角度间隔方向梯度统计的结果。</li>
	</ol></li>
</ol>4. 构建定向梯度特征向量
<ol><li>将样本划分为所需的计算区域，其中每个计算区域由四个相邻的模块组成，基于步骤 3.3 中获得的模块结果。例如，考虑 16 x 16 分辨率像素和 4 x 4 的块大小，图像分为 （16 / 4-1） x （ 16 / 4-1 ） = 9 个计算区域。</li>
	<li>计算计算区域内各块的梯度统计量的角度间隔内的方向梯度统计值。随后，得到以方向梯度统计量为分量的特征向量。</li>
	<li>组合来自每个计算区域的方向梯度特征向量，以获得图像的方向梯度特征向量。</li>
</ol>5. 支持向量机培训
<ol><li>从三种振动状态中随机选择 42 个样本创建训练组，剩余 18 个样本作为测试组。</li>
	<li>利用 MATLAB 的 fitcecoc 功能进行 SVM 训练;格式是 SVM = fitcecoc （trainingFeatures， Trainingeigenvalue） 其中SVM为待训练的支持向量机，trainingFeatures为训练组图像定向梯度特征向量，Trainingeigenvalue为训练组振动状态的特征值。非振动混凝土、振动混凝土和振动混凝土样品的振动状态特征值分别为 1、2 和 3。</li>
	<li>使用 Save 函数以 .mat 格式保存经过训练的 SVM 。</li>
</ol>6. SVM识别精度的验证
<ol><li>使用 MATLAB 的预测函数，将测试组样本图像的方向梯度特征向量输入到经过训练的 SVM 中，以获得每个测试样本的振动状态特征的计算值。格式如下： testgroupcalculateseigenvalues = predict （SVM， testFeature） 其中 testgroupcalculatesegenvalues 是振动状态特征的计算值，SVM 是在步骤 5 中训练的支持向量机。testFeature 是测试组样本图像的方向梯度特征向量。</li>
	<li>通过将测试集输入到经过训练的 SVM 中来确定测试集样本识别结果。计算测试集识别结果与实际状态匹配的样本数，然后通过将正确样本数除以测试集样本总数来计算识别准确率。<ol><li>如果测试识别准确率高于 94%，则认为 SVM 识别有效。如果低于 94%，则返回步骤 1.1 并调整二值化阈值、块大小 n 和方向梯度统计区间数 m。</li>
	</ol></li>
</ol>

用于识别混凝土振动状态的定向梯度直方图和 SVM

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作者没有什么可透露的。

本文利用支持向量机（SVM）学习各种混凝土振动状态样本的图像特征。基于机器学习结果，提出了一种基于图像识别的具体振动状态识别方法。为了提高识别精度，控制图像分割、图像二值化和定向梯度特征值提取这三个关键步骤的参数至关重要。根据测试结果，采用较小的二值化阈值对具体样品图像进行预处理，并利用128 pixels x 128 pixel的图像分割块大小。统计角度区间的方向梯度数设置为 12。...

混凝土是建筑行业广泛使用的基本建筑材料。在泵送过程中，混凝土经常产生空隙，需要通过振动压实。振动不足可能导致混凝土表面呈蜂窝状，而过度振动会导致混凝土离体 1,2。振动操作的质量显着影响成型混凝土结构的强度 3,4,5,6 和耐久性 7,8。Cai等[9,10]将实验研究与数值分析相结合，研究了振动对骨料沉降和混凝土耐久性的影响机制。结果表明，振动时间和骨料颗粒对骨料沉降有很大影响，而骨料密度和水泥基材料的塑性粘度影响最小。振动导致骨料沉积在混凝土试样的底部。此外，随着振动时间的增加，混凝土试样底部的氯离子浓度降低，而顶部的氯离子浓度显着增加9,10。
目前，混凝土振动状态的评估主要依赖于人工判断。随着建筑业通过智能化改革不断进步，机器人操作已成为未来的发展方向11,12。因此，智能振动操作的一个关键挑战是如何使机器人能够识别混凝土的振动状态。
定向梯度直方图是一种利用像素的强度梯度或边缘方向的分布作为描述符来表征图像中物体的表示和形状的技术13,14。这种方法在图像的局部网格单元上运行，在表征各种几何和光学条件下的图像变化时提供了强大的稳定性。
周等[15 提出了一种直接从拜耳模式图像中提取方向梯度特征的方法。通过将滤色器列与渐变算子进行匹配，这种方法省略了计算定向梯度的许多步骤，从而大大降低了定向渐变图像识别的计算要求。He et al.16 利用方向梯度直方图作为底层特征，采用平均聚类算法对钢轨紧固件进行分类，确定紧固件是否存在缺陷。识别结果表明，定向梯度特征直方图对紧固件缺陷具有较高的敏感性，满足铁路养护和维修的需要。在另一项研究中，Xu 等人 17 使用 Gabor 小波滤波对人脸图像特征进行了预处理，并通过二进制编码和 HOG 算法降低了特征向量的维度。该方法的平均识别准确率为92.5%。
支持向量机（SVM）18用于将向量映射到高维空间中，并建立具有合适方向的分离超平面，以最大化两个平行超平面之间的距离。这允许对支持向量进行分类 19.学者们对这种分类技术进行了改进和优化，使其在图像识别20,21，文本分类22，可靠性预测23和故障诊断24等各个领域得到应用。
Li等[25 ]开发了用于地震破坏模式识别的两阶段SVM模型，重点关注三种地震破坏模式。分析结果表明，所提出的两阶段支持向量机方法在3种失效模式下均能达到90%以上的准确率。Yang等[26 ]将优化算法与支持向量机相结合，模拟了5个超声参数与加载混凝土应力之间的关系。未优化的 SVM 的性能不尽如人意，尤其是在低应力阶段。然而，遍历由算法优化的模型会产生更好的结果，尽管计算时间很长。相比之下，粒子群优化优化的 SVM 显著缩短了计算时间，同时提供了最佳的仿真结果。Yan等[27 ]采用支持向量机技术，引入精度不敏感损失函数对高强混凝土的弹性模量进行预测，并将其预测精度与传统回归模型和神经网络模型进行比较。研究结果表明，与其他方法相比，SVM技术对弹性模量的预测误差更小。
本文收集了混凝土在各种振动状态下的图像样本，并利用定向梯度直方图技术描述了混凝土的不同状态。将定向梯度作为特征向量进行定向训练，重点关注使用定向梯度直方图-支持向量图技术识别混凝土振动状态的可行性。此外，还分析了方向梯度直方图特征提取过程中的二值化阈值、方向梯度统计块大小和方向梯度统计区间数这三个关键参数之间的影响机制，以及支持向量机的识别精度。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>camera</td>
			<td>SONY</td>
			<td>A6000</td>
			<td>The sensor size is 23.5x15.6mm, the maximum acquisition resolution is 1440 * 1080, and the effective pixel is 24.3 million.</td>
		</tr>
		<tr>
			<td>concrete</td>
			<td>Wuhan Construction Changxin Technology Development Co., Ltd.</td>
			<td>C30 pumping concrete</td>
			<td>According to the standard of &#39; concrete strength test and evaluation standard &#39; ( GB / T 50107-2010 ), the standard value of cubic compressive strength is 30 MPa pumping concrete.</td>
		</tr>
		<tr>
			<td>Matlab</td>
			<td>MathWorks</td>
			<td>Matlab R2017a</td>
			<td>MATLAB&#39;s programming interface provides development tools for improving code quality maintainability and maximizing performance. 
			It provides tools for building applications using custom graphical interfaces. 
			It provides tools for combining MATLAB-based algorithms with external applications and languages</td>
		</tr>
		<tr>
			<td>Processor&#160;</td>
			<td>Intel</td>
			<td>12th Gen Intel(R) Core (TM) i7-12700H @ 2.30GHz</td>
			<td>64-bit Win11 processor&#160;</td>
		</tr>
	</tbody>
</table>

image recognition and parameter analysis of concrete vibration state based on support vector machine

本文采用定向梯度直方图技术提取了不同振动状态下捕获的混凝土图像样本的特征。利用支持向量机（SVM）学习图像特征与振动状态之间的关系。机器学习结果随后用于评估混凝土振动状态的可行性。同时，分析了方向梯度直方图计算参数对识别精度的影响机理。结果验证了采用定向梯度直方图-SVM技术识别混凝土振动状态的可行性。识别准确率最初随着方向梯度的块大小或统计间隔数量的增加而增加，然后逐渐降低。识别准确率也随着二值化阈值的增加而线性降低。通过使用分辨率为1024 x 1024像素的样本图像并优化特征提取参数，可以达到100%的识别准确率。

该协议旨在分析方向梯度特征的三向量计算参数如何影响支持向量机识别混凝土振动状态的精度。方向梯度特征向量的主要计算参数包括方向梯度统计块大小、方向梯度统计角度区间数和二进制格雷阈值。本节使用三个主要计算参数作为变量来设计测试。测试参数级别详见 表 1。对分辨率为 1024 x 1024 像素的混凝土图像样本共进行了 100 次测试。与 表1 中描述的参数相对应...

Watch this Scientific Journal Video about Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines at JoVE.com

作者聚焦：使用定向梯度直方图技术和支持向量机进行高效图像识别 

本文所述的协议利用定向梯度直方图技术提取了各种振动状态下混凝土图像样品的特征。它采用支持向量机进行机器学习，从而产生了一种具有最小训练样本要求和低计算机性能要求的图像识别方法。

基于支撑矢量机的混凝土振动状态图像识别与参数分析

In this paper, the directional gradient histogram technology is employed to extract the features of concrete image samples captured under different ...

本文描述的协议利用定向梯度直方图技术提取了各种振动单元下混凝土图像样本的特征。它采用支持向量机进行机器学习，从而产生具有最小训练样本要求和低计算机性能要求的成像识别方法。这种方法大大减少了所需的样本数量，并降低了计算机性能要求。使用相当于 2.3 GHz 中央处理器的笔记本电脑，识别过程只需 50 秒即可完成支持的向量机的列车空间微分。使用 128 个项目和 128 个项目以下大小的图像分割。统计角度反转的方向向量数设置为 12。在224分辨率的图像处理过程中，机器学习结果的识别效果最佳。

image-recognition-parameter-analysis-concrete-vibration-state-based

Research

Education

JoVE Core

JoVE Journal

Civil Engineering

Engineering

Unit 1

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Mixing, Placing and Curing Concrete 

SCIENTISTS IN ACTION

852 次观看.  Wuhan University. 本文描述的协议利用定向梯度直方图技术提取了各种振动单元下混凝土图像样本的特征。它采用支持向量机进行机器学习，从而产生具有最小训练样本要求和低计算机性能要求的成像识别方法。这种方法大大减少了所需的样本数量，并降低了计算机性能要求。使用相当于 2.3 GHz 中央处理器的笔记本电脑，识别过程只需 50 秒即可完成支持的向量机的列车空间微分。使用 12...

视频: 作者聚焦：使用定向梯度直方图技术和支持向量机进行高效图像识别 

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces.&#160;Like the human eyes and brain, DFP uses triangulation between matching points in two views of the same scene at different angles to compute depth.&#160;However, unlike a stereo-based method, DFP uses a digital video projector to replace one of the cameras1. The projector rapidly projects a known sinusoidal pattern onto the subject, and the surface of the subject distorts these patterns in the camera&#8217;s field of view. Three distorted patterns (fringe images) from the camera can be used to compute the depth using triangulation.
Unlike other 3D measurement methods, DFP techniques lead to systems that tend to be faster, lower in equipment cost, more flexible, and easier to develop.&#160;DFP systems can also achieve the same measurement resolution as the camera.&#160;For this reason, DFP and other digital structured light techniques have recently been the focus of intense research (as summarized in1-5). Taking advantage of DFP, the graphics processing unit, and optimized algorithms, we have developed a system capable of 30&#160;Hz 3D video data acquisition, reconstruction, and display for over 300,000 measurement points per frame6,7.&#160;Binary defocusing DFP methods can achieve even greater speeds8.
Diverse applications can benefit from DFP techniques. Our collaborators have used our systems for facial function analysis9, facial animation10, cardiac mechanics studies11, and fluid surface measurements, but many other potential applications exist.&#160;This video will teach the fundamentals of DFP techniques and illustrate the design and operation of a binary defocusing DFP system.

This video describes the fundamentals of digital fringe projection techniques, which provide dense 3D measurements of dynamically changing surfaces.&#160;It also demonstrates the design and operation of a high-speed binary defocusing system based on these techniques.

Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces.&#160;Like the human eyes and brain, DFP uses ...

科研

工程学

Focused Ion Beam Fabrication of LiPON-based Solid-state Lithium-ion Nanobatteries for In Situ Testing

Solid-state electrolytes are a promising replacement for current organic liquid electrolytes, enabling higher energy densities and improved safety of lithium-ion (Li-ion) batteries. However, a number of setbacks prevent their integration into commercial devices. The main limiting factor is due to nanoscale phenomena occurring at the electrode/electrolyte interfaces, ultimately leading to degradation of battery operation. These key problems are highly challenging to observe and characterize as these batteries contain multiple buried interfaces. One approach for direct observation of interfacial phenomena in thin film batteries is through the fabrication of electrochemically active nanobatteries by a focused ion beam (FIB). As such, a reliable technique to fabricate nanobatteries was developed and demonstrated in recent work. Herein, a detailed protocol with a step-by-step process is presented to enable the reproduction of this nanobattery fabrication process. In particular, this technique was applied to a thin film battery consisting of LiCoO2/LiPON/a-Si, and has further been previously demonstrated by in situ cycling within a transmission electron microscope.

Focused Ion Beam Fabrication of LiPON-based Solid-state Lithium-ion Nanobatteries for In Situ Testing

A protocol for the fabrication of electrochemically active LiPON-based solid-state lithium-ion nanobatteries using a focused ion beam is presented.

基于 LiPON 的固态锂离子 Nanobatteries 的聚焦离子束制备方法在原位测试中的研究

Solid-state electrolytes are a promising replacement for current organic liquid electrolytes, enabling higher energy densities and improved safety of ...

Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors

Flexible photodetectors have been intensely studied for the use of curved image sensors, which are a crucial component in bio-inspired imaging systems, but several challenging points remain, such as a low absorption efficiency due to a thin active layer and low flexibility. We present an advanced method to fabricate a flexible phototransistor array with an improved electrical performance. The outstanding electrical performance is driven by a low dark current owing to deep impurity doping. Stretchable and flexible metal interconnectors simultaneously offer electrical and mechanical stabilities in a highly deformed state. The protocol explicitly describes the fabrication process of the phototransistor using a thin silicon membrane. By measuring I-V characteristics of the completed device in deformed states, we demonstrate that this approach improves the mechanical and electrical stabilities of the phototransistor array. We expect that this approach to a flexible phototransistor can be widely used for the applications of not only next-generation imaging systems/optoelectronics but also wearable devices such as tactile/pressure/temperature sensors and health monitors.

We present a detailed method to fabricate a deformable lateral NIPIN phototransistor array for curved image sensors. The phototransistor array with an open mesh form, which is composed of thin silicon islands and stretchable metal interconnectors, provides flexibility and stretchability. The parameter analyzer characterizes the electrical property of the fabricated phototransistor.

基于侧向 NIPIN Phototransistors 的柔性图像传感器的研制

Flexible photodetectors have been intensely studied for the use of curved image sensors, which are a crucial component in bio-inspired imaging systems, ...

Fabrication of Soft Pneumatic Network Actuators with Oblique Chambers

Soft pneumatic network actuators have become one of the most promising actuation devices in soft robotics which benefits from their large bending deformation and low input. However, their monotonous bending motion form in two-dimensional (2-D) space keeps them away from wide applications. This paper presents a detailed fabrication method of soft pneumatic network actuators with oblique chambers, to explore their motions in three-dimensional (3-D) space. The design of oblique chambers enables actuators with tunable coupled bending and twisting capabilities, which gives them the possibility to move dexterously in flexible manipulators, to become biologically inspired robots and medical devices. The fabrication process is based on the molding method, including the silicone elastomer preparation, chamber and base parts fabrication, actuator assembly, tubing connections, checks for leaks, and actuator repair. The fabrication method guarantees the rapid manufacturing of a series of actuators with only a few modifications in the molds. The test results show the high quality of the actuators and their prominent bending and twisting capabilities. Experiments of the gripper demonstrate the advantages of the development in adapting to objects with different diameters and providing sufficient friction.

Here we present a fabrication method of soft pneumatic network actuators with oblique chambers. The actuators are capable of generating coupled bending and twisting motions, which broadens their application in soft robotics.

斜腔软气动网络驱动器的研制

Soft pneumatic network actuators have become one of the most promising actuation devices in soft robotics which benefits from their large bending ...

A Polymer-based Piezoelectric Vibration Energy Harvester with a 3D Meshed-Core Structure

In this study, we fabricated a flexible 3D mesh structure with periodic voids by using a 3D lithography method and applying it to a vibration energy harvester to lower resonance frequency and increase output power. The fabrication process is mainly divided into two parts: three-dimensional photolithography for processing a 3D mesh structure, and a bonding process of piezoelectric films and the mesh structure. With the fabricated flexible mesh structure, we achieved the reduction of resonance frequency and improvement of output power, simultaneously. From the results of the vibration tests, the meshed-core-type vibration energy harvester (VEH) exhibited 42.6% higher output voltage than the solid-core-type VEH. In addition, the meshed-core-type VEH yielded 18.7 Hz of resonance frequency, 15.8% lower than the solid-core-type VEH, and 24.6 &#956;W of output power, 68.5% higher than the solid-core-type VEH. The advantage of the proposed method is that a complex and flexible structure with voids in three dimensions can be relatively easily fabricated in a short time by the inclined exposure method. As it is possible to lower the resonance frequency of the VEH by the mesh structure, use in low-frequency applications, such as wearable devices and house appliances, can be expected in the future.

In this study, we fabricated a flexible 3D mesh structure and applied it to the elastic layer of a bimorph cantilever-type vibration energy harvester for the purpose of lowering resonance frequency and increasing output power.

一种基于聚合物的三维介心结构压电振动能量收割机

In this study, we fabricated a flexible 3D mesh structure with periodic voids by using a 3D lithography method and applying it to a vibration energy ...

Crack Monitoring in Resonance Fatigue Testing of Welded Specimens Using Digital Image Correlation

A procedure using digital image correlation (DIC) to detect cracks on welded specimens during fatigue tests on resonance testing machines is presented. It is intended as a practical and reproducible procedure to identify macroscopic cracks at an early stage and monitor crack propagation during fatigue tests. It consists of strain field measurements at the weld using DIC. Images are taken at fixed load cycle intervals. Cracks become visible in the computed strain field as elevated strains. This way, the whole width of a small-scale specimen can be monitored to detect where and when a crack initiates. Subsequently, it is possible to monitor the development of the crack length. Because the resulting images are saved, the results are verifiable and comparable. The procedure is limited to cracks initiating at the surface and is intended for fatigue tests under laboratory conditions. By visualizing the crack, the presented procedure allows direct observation of macrocracks from their formation until rupture of the specimen.

Digital image correlation is used in fatigue tests on a resonance testing machine to detect macroscopic cracks and monitor crack propagation in welded specimens. Cracks on the specimen surface become visible as increased strains.

使用数字图像相关性对焊接试样共振疲劳测试中的裂纹监测

A procedure using digital image correlation (DIC) to detect cracks on welded specimens during fatigue tests on resonance testing machines is presented. It ...

Deep Neural Networks for Image-Based Dietary Assessment

Due to the issues and costs associated with manual dietary assessment approaches, automated solutions are required to ease and speed up the work and increase its quality. Today, automated solutions are able to record a person's dietary intake in a much simpler way, such as by taking an image with a smartphone camera. In this article, we will focus on such image-based approaches to dietary assessment. For the food image recognition problem, deep neural networks have achieved the state of the art in recent years, and we present our work in this field. In particular, we first describe the method for food and beverage image recognition using a deep neural network architecture, called NutriNet. This method, like most research done in the early days of deep learning-based food image recognition, is limited to one output per image, and therefore unsuitable for images with multiple food or beverage items. That is why approaches that perform food image segmentation are considerably more robust, as they are able to identify any number of food or beverage items in the image. We therefore also present two methods for food image segmentation - one is based on fully convolutional networks (FCNs), and the other on deep residual networks (ResNet).

The goal of the work presented in this article is to develop technology for automated recognition of food and beverage items from images taken by mobile devices. The technology comprises of two different approaches - the first one performs food image recognition while the second one performs food image segmentation.

基于图像的饮食评估深度神经网络

Due to the issues and costs associated with manual dietary assessment approaches, automated solutions are required to ease and speed up the work and ...

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Recently, deep learning-based segmentation models have been widely applied in the ophthalmic field. This study presents the complete process of constructing an orbital computed tomography (CT) segmentation model based on U-Net. For supervised learning, a labor-intensive and time-consuming process is required. The method of labeling with super-resolution to efficiently mask the ground truth on orbital CT images is introduced. Also, the volume of interest is cropped as part of the pre-processing of the dataset. Then, after extracting the volumes of interest of the orbital structures, the model for segmenting the key structures of the orbital CT is constructed using U-Net, with sequential 2D slices that are used as inputs and two bi-directional convolutional long-term short memories for conserving the inter-slice correlations. This study primarily focuses on the segmentation of the eyeball, optic nerve, and extraocular muscles. The evaluation of the segmentation reveals the potential application of segmentation to orbital CT images using deep learning methods.

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

An object segmentation protocol for orbital computed tomography (CT) images is introduced. The methods of labeling the ground truth of orbital structures by using super-resolution, extracting the volume of interest from CT images, and modeling multi-label segmentation using 2D sequential U-Net for orbital CT images are explained for supervised learning.

基于深度学习的医学图像分割在轨道计算机断层扫描 中的 应用

Recently, deep learning-based segmentation models have been widely applied in the ophthalmic field. This study presents the complete process of ...

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

There is considerable scientific interest in understanding the strains that tendon cells experience in situ and how these strains influence tissue remodeling. Based on this interest, several analytical techniques have been developed to measure local tissue strains within tendon explants during loading. However, in several cases, the accuracy and sensitivity of these techniques have not been reported, and none of the algorithms are publicly available. This has made it difficult for the more widespread measurement of local tissue strains in tendon explants. Therefore, the objective of this paper was to create a validated analysis tool for measuring local tissue strains in tendon explants that is readily available and easy to use. Specifically, a publicly available augmented-Lagrangian digital image correlation (ALDIC) algorithm was adapted for measuring 2D strains by tracking the displacements of cell nuclei within mouse Achilles tendons under uniaxial tension. Additionally, the accuracy of the calculated strains was validated by analyzing digitally transformed images, as well as by comparing the strains with values determined from an independent technique (i.e., photobleached lines). Finally, a technique was incorporated into the algorithm to reconstruct the reference image using the calculated displacement field, which can be used to assess the accuracy of the algorithm in the absence of known strain values or a secondary measurement technique. The algorithm is capable of measuring strains up to 0.1 with an accuracy of 0.00015. The technique for comparing a reconstructed reference image with the actual reference image successfully identified samples that had erroneous data and indicated that, in samples with good data, approximately 85% of the displacement field was accurate. Finally, the strains measured in mouse Achilles tendons were consistent with the prior literature. Therefore, this algorithm is a highly useful and adaptable tool for accurately measuring local tissue strains in tendons.

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

This paper describes an open-source digital image correlation algorithm for measuring local 2D tissue strains within tendon explants. The accuracy of the technique has been validated using multiple techniques, and it is available for public use.

通过开源数字图像相关 测量 肌腱中的局部组织应变

There is considerable scientific interest in understanding the strains that tendon cells experience in situ and how these strains influence tissue ...

纳米纤维素纸基分析装置的微压花制备  

Microembossing: A Convenient Process for Fabricating Microchannels on Nanocellulose Paper-Based Microfluidics

Nanopaper, derived from nanofibrillated cellulose, has generated considerable interest as a promising material for microfluidic applications. Its appeal lies in a range of excellent&#160;qualities, including an exceptionally smooth surface, outstanding optical transparency, a uniform nanofiber matrix with nanoscale porosity, and customizable chemical properties. Despite the rapid growth of nanopaper-based microfluidics, the current techniques used to create microchannels on nanopaper, such as 3D printing, spray coating, or manual cutting and assembly, which are crucial for practical applications, still possess certain limitations, notably susceptibility to contamination. Furthermore, these methods are restricted to the production of millimeter-sized channels. This study introduces a straightforward process that utilizes convenient plastic micro-molds for simple microembossing operations to fabricate microchannels on nanopaper, achieving a minimum width of 200 &#181;m. The developed microchannel outperforms existing approaches, achieving a fourfold improvement, and can be fabricated within 45 min. Furthermore, fabrication parameters have been optimized, and a convenient quick-reference table is provided for application developers. The proof-of-concept for a laminar mixer, droplet generator, and functional nanopaper-based analytical devices (NanoPADs) designed for Rhodamine B sensing using surface-enhanced Raman spectroscopy was demonstrated. Notably, the NanoPADs exhibited exceptional performance with improved limits of detection. These outstanding results can be attributed to the superior optical properties of nanopaper and the recently developed accurate microembossing method, enabling the integration and fine-tuning of the NanoPADs.

作者聚焦：通过纳米纸上的微通道制造彻底改变微流体 

This protocol describes a straightforward process that utilizes convenient plastic micro-molds for simple microembossing operations to fabricate microchannels on nanofibrillated cellulose paper, achieving a minimum width of 200 &#181;m.

微压花：在纳米纤维素纸基微流控上制造微通道的便捷工艺

Nanopaper, derived from nanofibrillated cellulose, has generated considerable interest as a promising material for microfluidic applications. Its appeal ...