暗模式是指数字平台经营者采用界面设计、诱导信息、虚假信息等方式,通过阻碍用户行使权利、降低决策能力、陷入错误认知,诱导、误导、强迫平台用户作出违背真实意愿的行为决策。暗模式普遍存在于各类市场应用中,且由于隐蔽性、操纵性...暗模式是指数字平台经营者采用界面设计、诱导信息、虚假信息等方式,通过阻碍用户行使权利、降低决策能力、陷入错误认知,诱导、误导、强迫平台用户作出违背真实意愿的行为决策。暗模式普遍存在于各类市场应用中,且由于隐蔽性、操纵性和群体性特点难以被识别和治理。美国、欧盟、印度等国家(地区)通过专门立法规制暗模式,但暗模式的规范化以及规制边界等问题仍有待厘清。规制暗模式的理论基础包括用户视角的有限理性和平台视角的主体责任,具体体现为数字平台作为规则制定者的公平诚信义务、基础设施运营者的中立义务以及数据受托者的信义义务。在暗模式规制从权利保护路径逐渐走向行政合规路径的背景下,监管者可针对数字平台暗模式采用风险分级的规制方案,辅以Fairness by Design的设计理念实现暗模式的光明化转变。展开更多
For Automatic Optical Inspection (AOI) machines that were introduced to Printed Circuit Board market more than five years ago, illumination technique and light devices are outdated. Images captured by old AO...For Automatic Optical Inspection (AOI) machines that were introduced to Printed Circuit Board market more than five years ago, illumination technique and light devices are outdated. Images captured by old AOI machines are not easy to be recognized by typical optical character recognition (OCR) algorithms, especially for dark silk. How to effectively increase silk recognition accuracy is indispensable for improving overall production efficiency in SMT plant. This paper uses fine tuned Character Region Awareness for Text Detection (CRAFT) method to build model for dark silk recognition. CRAFT model consists of a structure similar to U-net, followed by VGG based convolutional neural network. Continuous two-dimensional Gaussian distribution was used for the annotation of image segmentation. CRAFT model is good at recognizing different types of printed characters with high accuracy and transferability. Results show that with the help of CRAFT model, accuracy for OK board is 95% (error rate is 5%), and accuracy for NG board is 100% (omission rate is 0%).展开更多
文摘暗模式是指数字平台经营者采用界面设计、诱导信息、虚假信息等方式,通过阻碍用户行使权利、降低决策能力、陷入错误认知,诱导、误导、强迫平台用户作出违背真实意愿的行为决策。暗模式普遍存在于各类市场应用中,且由于隐蔽性、操纵性和群体性特点难以被识别和治理。美国、欧盟、印度等国家(地区)通过专门立法规制暗模式,但暗模式的规范化以及规制边界等问题仍有待厘清。规制暗模式的理论基础包括用户视角的有限理性和平台视角的主体责任,具体体现为数字平台作为规则制定者的公平诚信义务、基础设施运营者的中立义务以及数据受托者的信义义务。在暗模式规制从权利保护路径逐渐走向行政合规路径的背景下,监管者可针对数字平台暗模式采用风险分级的规制方案,辅以Fairness by Design的设计理念实现暗模式的光明化转变。
文摘For Automatic Optical Inspection (AOI) machines that were introduced to Printed Circuit Board market more than five years ago, illumination technique and light devices are outdated. Images captured by old AOI machines are not easy to be recognized by typical optical character recognition (OCR) algorithms, especially for dark silk. How to effectively increase silk recognition accuracy is indispensable for improving overall production efficiency in SMT plant. This paper uses fine tuned Character Region Awareness for Text Detection (CRAFT) method to build model for dark silk recognition. CRAFT model consists of a structure similar to U-net, followed by VGG based convolutional neural network. Continuous two-dimensional Gaussian distribution was used for the annotation of image segmentation. CRAFT model is good at recognizing different types of printed characters with high accuracy and transferability. Results show that with the help of CRAFT model, accuracy for OK board is 95% (error rate is 5%), and accuracy for NG board is 100% (omission rate is 0%).
