What does OCR mean What does cro mean

In **, CRO generally refers to CRO concept stocks.

CRO concept stock refers to the concept stock of pharmaceutical R&D contract outsourcing service institutions, and pharmaceutical R&D contract outsourcing refers to the provision of professional outsourcing services for drug research and development of pharmaceutical enterprises through contracts.

CRO stands for "Contract Research Organization" model of great significance to the pharmaceutical industry, which can provide research services to pharmaceutical companies in a short period of time. In this way, it helps to shorten the R&D cycle of new drugs, which is conducive to improving the speed of new drugs on the market of pharmaceutical companies and reducing the management and R&D expenses of pharmaceutical companies.

According to the nature of the work, CRO is roughly divided into pre-clinical research CRO and clinical research CRO, and clinical research CRO is mainly commissioned clinical trial.

Overview of the development of CROs

CRO can be used as a kind of borrowable external resource for pharmaceutical companies, which can quickly organize a clinical research team with a high degree of specialization and rich clinical research experience in a short period of time, and can reduce the management costs of the entire pharmaceutical enterprise. It is with these unique advantages that CRO is able to provide technical support and professional services to the pharmaceutical industry in these aspects.

As an emerging industry, CRO originated in the United States since the early 80s of the 20th century. With the continuous tightening and improvement of the US FDA's regulations on the research and development of new drugs, the drug research and development process has become more complex, time-consuming and costly, and pharmaceutical companies are gradually facing various pressures from the following aspects.

It can be seen that in order to survive and thrive in such an increasingly tightly regulated and competitive environment, pharmaceutical companies must try to shorten the time spent on new drug research and development, while at the same time controlling costs and reducing the risk of failure. The key to resolving this contradiction lies in obtaining high-quality research and successfully grasping every strategic decision throughout the new drug development process.

OCR is the abbreviation of Optical Character Recognition, OCR technology is simply to convert text information into image information, and then use text recognition technology to convert image information into input technology that can be used.

Functions of OCR::

1. OCR recognition technology not only has the ability to automatically judge, split, identify and restore a variety of general-purpose printed materials, but also makes satisfactory practical results in understanding.

2. OCR can automatically analyze the layout of the manuscript, automatically divide the columns, and judge the corresponding attributes such as title, horizontal column, image, **, etc., and determine the recognition order, and restore the recognition results into a new text consistent with the layout of the scanned document.

3. OCR can also support ** automatic entry technology, which can automatically identify specific ** printed or printed Chinese characters, letters and numbers, and can recognize handwritten Chinese characters, handwritten letters, numbers and a variety of handwritten symbols, and output them in ** format. It improves the efficiency of entry and saves a lot of manpower.

OCR means Optical Character Recognition in Chinese.

OCR (Optical Character Recognition) refers to the process in which an electronic device (such as a scanner or digital camera) examines the characters printed on paper, determines their shape by detecting dark and light patterns, and then uses character recognition methods to translate the shapes into computer text.

OCR is a technology that converts the text in the paper document into a black-and-white dot matrix image file by optical means for printed characters, and converts the text in the image into text format through recognition software for further processing by word processing software.

OCR is the abbreviation of Optical Character Recognition, which means: Character Recognition.

OCR (Optical Character Recognition) refers to the process of electronic devices (such as scanners or digital cameras) checking the characters printed on paper, and then using character recognition methods to translate the shapes into computer words. That is, the process of scanning text materials, and then analyzing and processing image files to obtain text and layout information.

How to debug or use auxiliary information to improve the accuracy of recognition is the most important issue of OCR. The main indicators to measure the performance of an OCR system are: rejection rate, false acceptance rate, recognition speed, user-friendliness, product stability, ease of use and feasibility, etc.

To put it simply, OCR is to recognize and transcribe the text information in an image

OCR transcription annotation is a very important type of annotation in the field of data annotation, and the annotated data is also used in AI machine learning.

What does OCR mean, simply put, it is to recognize the text on **, and then save the text on ** to the document;

In detail: the computer is recognized by OCR technology, that is, optical character recognition technology. For example, Swift OCR text recognition is used to convert ** text through this technology.

Using OCR, image processing and second-level full-text retrieval technologies, unstructured data is transformed into structured data for strategic analysis, and document image enhancement processing can be carried out

Fuzzy search, multi-condition and multi-keyword search, automatic document classification, review and sharing, and big data analysis.

OCR is a kind of recognition technology, and now OCR text recognition software is used to recognize text, and OCR text recognition software is very good.

OCR (Optical Character Recognition) refers to the process of electronic devices (such as scanners or digital cameras) checking the characters printed on paper, determining their shape by detecting dark and light patterns, and then translating the shape into computer text using character recognition methods. That is, for printed characters, the text in the paper document is converted into a black and white dot matrix image file by optical means, and the text in the image is converted into text format through recognition software for further processing by word processing software.

OCR is a tug-of-war technology with recognition rate, which is used to scan Chinese characters such as ** or pdf and convert them into word format or txt format. To put it bluntly, it is a software that transforms from ** to document, and the effective OCR text recognition software is very easy to use, with high recognition accuracy.

OCR is an optical character recognition technology, and RPA is very effective in automating daily operations, but since RPA only runs on personal computers, manually entering information on paper media, it is difficult to achieve complete automation with RPA alone, so OCR technology is used. OCR can automatically recognize and read the content of paper documents and transmit them to the computer, and then perform the work assigned to you by RPA. In this regard, I personally recommend that it is really smart, and it has done a very good job in the combination of RPA and AI technology.

OCR is the abbreviation of "Optical Character Recognition", translated as Optical Character Recognition, which refers to the process of electronic devices (such as scanners or digital cameras) checking the characters printed on paper, determining their shape by detecting dark and light patterns, and then translating the shape into computer text with character recognition methods. And through the recognition software to convert the text in the image into text format, for the word processing software to further process the technology. It can be applied to the input and processing of bank bills, a large number of written materials, archives and documents. It is suitable for automatic scanning and identification and long-term storage of a large number of bills** in banking, taxation and other industries.

Compared with other texts, OCR technology is usually evaluated based on four aspects: final recognition rate, recognition speed, layout comprehension accuracy and layout restoration satisfaction.

It can be applied to the input and processing of bank bills, a large number of written materials, archives and documents. It is suitable for automatic scanning and identification and long-term storage of a large number of bills** in banking, taxation and other industries. Compared with other texts, OCR technology is usually evaluated based on four aspects: final recognition rate, recognition speed, layout comprehension accuracy and layout restoration satisfaction.

With the rise of artificial intelligence, people are pursuing a simpler job, and OCR recognition technology can make the work easier.

Main applications in life:

1. OCR certificate recognition.

The OCR recognition technology of documents was based on PC at the beginning, and in recent years, it has begun to develop to the mobile terminal, mainly including Android and iOS platform SDKs, and the current mature ID card recognition, driving license recognition, driver's license recognition, passport recognition, etc.

2. OCR license plate recognition:

OCR license plate recognition is divided into DSP embedded recognition, Android iOS license plate recognition, parking space detection, and central network encryption recognition.

3. OCR car VIN code recognition:

The data is automatically parsed through the VIN code, and the car configuration and parameters are clear at a glance.

OCR (Optical Character Recognition) refers to the process of electronic devices (such as scanners or digital cameras) checking the characters printed on paper, and then using character recognition methods to translate the shapes into computer words. Due to the popularity and wide application of scanners, OCR software only needs to provide an interface with the scanner and use the scanner driver software. Therefore, OCR software is mainly composed of the following parts:

1. Image input and preprocessing

Image input: For different image formats, there are different storage formats and different compression methods. Pre-processing: mainly including binarization, noise removal, tilt correction, etc.

2. Binarization:

For the content of the camera, we can simply divide it into foreground and back leakage, in order to make the computer faster and better recognize the text, we need to process the color map first, so that only the foreground information and background information can be simply defined as black, and the background information is white, which is the binary map.

3. Noise removal:

For different documents, we can define noise differently, and denoising according to the characteristics of the noise is called noise removal.

4. Tilt is correct:

Because the general user, when taking a photo of a document, are more casual, so the image out of the ** inevitably produces tilt, which requires text recognition software to correct.

Layout analysis: 5. The process of dividing the document into paragraphs and branches is called layout analysis, because of the actual document. Variety, complexity, and therefore, there is no fixed, optimal cutting model.

6. Character cutting:

Due to the limitation of photographic conditions, it often causes character adhesion and pen breakage, so the performance of the recognition system is greatly limited, which requires the text recognition software to have a character cutting function.

7. Character recognition

This research is already a very early thing, there was template matching relatively early, and later it was mainly based on feature extraction, due to the displacement of text, the thickness of strokes, broken strokes, adhesion, rotation and other factors, which greatly affected the difficulty of feature extraction.

8. Layout restoration:

People want the recognized text to still be arranged like the original document, with the same paragraphs, the same position, the same order, and the output to the word document, pdf document, etc., this process is called layout restoration.

9. Post-processing and proofreading:

According to the relationship between the specific language context, the recognition result is corrected, which is post-processing.

The purpose of developing an OCR text recognition software system is very simple, just to make a conversion of the image, so that the graphics in the image continue to be saved, and the data and the text in the image will be turned into computer text if there is a delay, so that the storage capacity of the image data can be reduced, the recognized text can be reused and analyzed, and of course, it can also save the manpower and time for keyboard input.

From the image to the output of the result, it must go through the input of the image of the image of the shadow back to the ear, the image pre-processing, the extraction of text features, the comparison and recognition, and finally the correction of the wrong text through manual correction, and the output of the result.