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Working languages:
English to Chinese Chinese to English
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Services
Translation, Editing/proofreading, AI + Human review (MT post-editing), Software localization
Expertise
Specializes in:
Patents
Law: Patents, Trademarks, Copyright
IT (Information Technology)
Computers: Software
Computers: Systems, Networks
Electronics / Elect Eng
Mechanics / Mech Engineering
Mathematics & Statistics
Physics
Internet, e-Commerce
Also works in:
Automotive / Cars & Trucks
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Volunteer / Pro-bono work
Open to considering volunteer work for registered non-profit organizations
Rates
General rate: 0.08 USD per word / 30 USD per hour
Rates per language pair: English to Chinese - Standard rate: 0.08 USD per word / 30 USD per hour Chinese to English - Standard rate: 0.08 USD per character / 30 USD per hour
Chinese to English: CN-EN Sample-_-Machine Learning General field: Law/Patents Detailed field: Computers (general)
Source text - Chinese 1、一种基于多模态数据异构Transformer资产识别方法,其特征在于,包括下述步骤:
采集资产各个模态的信息,包括文本信息和图像信息;
构建ALBERT模型、ViT模型和CLIP模型;
基于ALBERT模型进行文本信息特征提取,通过多层的Transformer编码器学习文本序列中的上下文关系,将ALBERT模型的输出连接到全连接层并输出最终的分类信息;
基于ViT模型进行图像信息特征提取,将图像信息划分成令牌,经过Transformer编码器对图像信息划分后的内容信息进行捕捉学习,经过分类头将图像特征映射成类别信息;
基于CLIP模型进行图像文本匹配信息特征提取,构造图像及与其匹配的文字描述样本对,将图像和文本信息进行编码后得到图像和文本的特征表示向量,图像和文本的特征表示向量线性投影到多模态空间中,计算两种模态的相似度,得到图像信息与文本信息的匹配度;
对不同模态的信息进行不同通道的资产类型识别,输出不同通道的分类信息,基于CLIP模型对资产缺失信息进行生成;
将不同通道的分类信息与CLIP模型得到的图像信息与文本信息的匹配度进行判别融合,输出最终的资产类别信息。
Translation - English 1. A multimodal data heterogeneous Transformer-based asset recognition method, comprising:
collecting various-modal information of an asset, comprising text information and image information;
building an A Lite Bidirectional Encoder Representations from Transformers, ALBERT, model, a Vision Transformer, ViT, model, and a Contrastive Language-Image Pre-Training, CLIP, model;
by the ALBERT model, extracting a text information feature: using a multilayer Transformer encoder to learn a context relation in a text sequence; connecting an output of the ALBERT model to a fully connected layer; and outputting final classification information;
by the ViT model, extracting an image information feature: dividing the image information into tokens; using a Transformer encoder to capture and learn content information from the dividing of the image information; and using a classification head to map an image feature to class information;
by the CLIP model, extracting image-text matching information feature: building an image with matching text description sample pair; encoding the image information and the text information to obtain an image feature representation vector and a text feature representation vector; linearly projecting the image feature representation vector and the text feature representation vector into a multimodal space; calculating a similarity between two modalities to obtain a matching degree between the image information and the text information;
by different channels, applying asset type recognition to information in different modalities; outputting classification information from the different channels; by the CLIP model, generating asset void information; and
discriminatively fusing the classification information from the different channels with the matching degree between the image information and the text information obtained by the CLIP model, and outputting final asset class information.
English to Chinese: EN-CN Sample-_-Automotive General field: Law/Patents Detailed field: Automotive / Cars & Trucks
Source text - English WHAT IS CLAIMED IS:
1. A corner module apparatus for a vehicle, comprising:
a knuckle coupled to a wheel bearing rotatably supporting a wheel;
a drive motor disposed in such a manner as to be spaced a distance away from the wheel and configured to generate a drive power;
a transfer shaft module provided between the wheel and the drive motor and configured to transfer the drive power generated from the drive motor;
a suspension unit connected to the knuckle and configured to absorb shock transferred from a road surface; and
a steering unit configured to support the drive motor and the suspension unit and to adjust a steering wheel of the wheel.
Translation - Chinese 1. 一种用于车辆的角模块装置,包括:
转向节,接合到可旋转地支撑车轮的车轮轴承;
驱动电机,被设置为与所述车轮间隔开一定距离,并被配置为产生驱动力;
传动轴模块,提供在所述车轮和所述驱动电机之间,并被配置为传递从所述驱动电机产生的驱动力;
悬挂单元,连接到所述转向节,并被配置为吸收从路面传递的冲击;以及
转向单元,被配置为支撑所述驱动电机和所述悬挂单元,并调节所述车轮的方向盘。
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Experience
Years of experience: 13. Registered at ProZ.com: Jul 2025.
This is a short personal account on how I became a certified patent agent on oversea patents.
It all began years ago when my supervisor told me I have a NEGATIVE client feedback. The assignment was something about law.
To my defense, I did give the task my all. Unfortunately, although I had two university degrees, law was not among them, and was understandably not really my strongest suit.
However, one of the reasons why I chose a career in translation was to learn new things while winning my bread, so I began taking law courses in Coursera after work. The experience turn out to be quite pleasant! I really liked legal theories, and began seriously considering a career in law.
But by then, I had already passed my 30s. In China, that is considered a rather risky moment to radically shift one's profession. Besides, competing with law majors at my age would not seem very wise. All I had was my degrees in computer science and material physics, and my experience in translation, so better make the most out them.
That was how patent law, a combination of technology and legal disciplines, introduced itself. I began offering my services to patent law firms, and they were pleased by my work. After a year or so, I took a full time position in one of them, and eventually passed the bar exam to become a certified patent agent.
Thanks for reaching here! Hope the above could help you know me better.
Keywords: computers, information technology, software, artificial intelligence, machine learning, LLM