NotAfraidOfWong

What is OCR (Optical Character Recognition)? OCR is a tool to allow computers to recognize the text from physical documents to be interpreted as data. When we read text on a document, whether it’s on physical paper or on the computer screen, we instantly know what letter or other symbols it is. However, for computers, it’s a little more complicated. Certain programs use OCR to allow you to edit the text from the scanned document like you would in a word processor. You can highlight text, copy it to other documents or rewrite whole sections. Another use for OCR is to make full-text searching a possibility. Some OCR programs will add the text recognized from a scanned document as metadata to the file, allowing certain programs to search for the document using any text contained within the document. Applications Widely used as a form of information entry from printed paper data records – whether passport documents, invoices, bank statements , computerized receipts, business cards,...

CNN Performance Factors It is very hard to have a fair comparison among different object detectors. There is no straight answer on which model is the best. For real-life applications, we make choices to balance accuracy and speed. Besides the detector types, we need to aware of other choices that impact the performance: 1) Feature Extractors (VGG16, ResNet, Inception, MobileNet) Feature extraction is a process of dimensionality reduction by which an initial set of raw data is reduced to more manageable groups for processing. Feature extraction is the name for methods that select and/or combine variables into features, effectively reducing the amount of data that must be processed, while still accurately and completely describing the original data set. A CNN is composed of two basic parts of feature extraction and classification . Feature extraction includes several convolution layers followed by max-pooling and an activation function. The classifier usually consists of fully c...