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Optical The Character Recognition Pipeline: Detection of Text and Segmentation Introduction A very crucial modules in the optical character recognition pipelines is segmentation and detection of text, which is also known "text-localization". As we discussed in the prior blog we discussed several methods for pre-processing the image input that can aid in increasing the OCR accuracy by collection various documents or we can say gathering OCR Datasets . The blog in this one, we'll discover how to locate the text in an image to cut them out, and later feed them into our text recognition program to detect text in it. What is text detection and segmentation? It's the process of locating every instances of text on the photo into meaningful parts like words, characters, or text lines. Make segments of each of these components. The method of character-based identification first recognizes the individual characters , and then groups the characters into words. One method for doi

How can you improve AI Security Camera Performance with Image Annotation Services? Introduction Security cameras are used for home security and 24/7 surveillance is becoming more common among people across the globe. Also, keeping an eye on your home is essential to ensure that your family members and home protected from robbery, theft and criminals as well as any other type of unauthorized person who may hurt you or cause damage to the property located on the property. AI-based cameras are able to provide advanced security features for homes and surveillance systems for commercial buildings. To train the AI cameras for surveillance it is necessary to have a massive amount of training data sets are required which can be accomplished with annotation images that are labeled so as to make various objects easy to identify and boost the efficiency of AI security by providing high-quality images services. Image ANOTTATIONS FOR AI SECURITY CAMERAS Annotation for Identifying the people in the

Everything About Data annotation for Machine Learning Models What is Data Annotations? Annotation of data is the act of labelling data in various formats, such as images, text or video. In order to train machine learning, supervised, labels are needed for Audio, Text, Image or Video Dataset to allow machines to easily and effectively comprehend the patterns of input. What is a data annotator supposed to do? Data annotation (commonly called data labelling) is a key element in ensuring that your AI or machine-learning projects are armed using the right amount of data to draw lessons from. Annotators are required to locate and label specific data so that machines can recognize and categorize information. Why is data annotation so important? Annotated data that is properly interpreted is essential for the development of autonomous vehicles as well as computer vision for drones flying in the air as well as different AI as well as robotics-related applications. Autonomous vehicles have to be

Video Recognition using Deep Learning Introduction Deep learning-based solutions for video recognition is primarily about the detection, classification and localization of static, multi-class objects in the field of view, and plotting the changing form factors, pose, orientation and position of objects in time. The most popular use case is to analyze how human actors within the field of vision. There are a variety of solutions utilized in the Deep Computer Vision community to enhance the pipeline's throughput, utilization of resources (specifically when inference is performed using edge devices with compute constraints) in addition to performance (accuracy and response). In this blog, we'll explore the many options for inputs, solutions and design considerations that are applied to recognition of collected Video Dataset by using methods of deep learning. What are the most common video datasets used to train models? Deep learning models to train for different video analysis tas

The importance to Image Annotation Services Image Annotation to Machine Learning Services for image annotation provide annotations of all kinds and sizes of images using precise tools for capturing, making images easily recognizable by machines. We use the most effective methods and tools to annotation images of different fields, providing the data for training to machine learning and AI in many subfields. The annotation of the data especially image annotations an essential step to train models. When annotations are used to create a algorithm, the precision will be greater for the case of any AI project. Image Annotation Services as well as other tags are now a important part of the businesses in diverse industries that are growing. After all images have been properly labeled and annotated, they are fed to the algorithms to help train the model and achieve precise results. Under Data Annotation , The role of annotation services for images is becoming increasingly important when it com

Making use of AI and deep Learning to Summarize Videos Introduction The video market in the world is now the center of attention according to Forbes more than 500 million minutes of video content are seen by users on YouTube each day. Google also states that nearly 50 % of users are looking for videos related to a service or product prior to visiting a shop. Numerous such figures show that video content is growing , and will remain popular for sharing information. Already, we are seeing the shift away from text and copy to snap stories and images (e.g. Instagram) to share the content. AI (AI) can play a significant role in the shift towards video. AI can be used AI to enhance video quality through stabilization, and to better understand to classify and collect Video Dataset content for editing and to deliver better and reach. AI also plays an important role in video summarization. It is a process that reduces the length of a film by picking keyframes or portions of video that convey t

Talk Recognition: How to Speak to Your Chatbot Introduction The capability to communicate audio via chatbots is thanks to a technology called Speech Recognition, and this is what we'll be talking about in this post. If you're interested and want to learn more about the advantages of this feature for chatbots, keep reading! What exactly is Speech Recognition? The past was that the idea of robots helping you with specific tasks was an idea from a movie. However, much faster than we anticipated chatbots were appearing. Then, after a while the chatbots grew and began talking to us and with us. them. Speech Recognition is a branch of Computer Science and Computational Linguistics. Alongside Speech Recognition, this technology is often referred to in other names such as Speech Recognition, ASR (Automatic Speech Recognition), Computer Speech Recognition as well as Speech to Text (STT). What is Speech Recognition work? Like the name suggests, this technology is capable of recognizing v

What is the Process by which OCR extract text from images? What exactly is OCR? This online application utilizes sophisticated algorithms to extract text from an images with Optical Character Recognition. It is also referred to as an image-to-text tool. OCR is also known as Optical Character Recognition is a technology that detects the characters of an alphabet and assists in manipulate them using different tools. Before you begin to work with it you must be aware of its history. The evolution of OCR The image-to-text converter that we use today isn't identical to the one developed by the company for the very first time. Its story is filled with twists and turns, bringing our back in time to beginning of the nineteenth century. Children do not come with the ability to read and comprehend written script , even in their native language. They build up muscles slowly and eventually are able to read handwriting. However, the current OCR Training Dataset is up to in recognizing any type

What is Video? Annotation for Deep Learning Introduction An annotation process for video is identifying videos. This process is used to make it a suitable data set for the training of deep-learning (DL) or machine learning (ML) algorithms. The neural networks that are pre-trained can then be used in computer vision-related applications for example, like automated software for video classifying. ML is a branch that studies Artificial Intelligence (AI) research that dates back to the 1940s. It was the time that artificial networks were created to replicate the tasks and workflows that the brain of humans. Yet, ML is now categorized as a narrow AI research. It remains largely different by AGI (artificial general intelligence). In addition, deep learning is an additional field within ML. This is a field that deals with bigger artificial neural networks that are trained with larger amounts of data. This sub-field was created with the advent of computers that were more powerful to be used to

What exactly is Text Classification What's Text Classification? Text Classification is the method of categorizing text into several different categories to structure, organize and filter out any type of parameter. For instance, the process of classification of text is utilized in medical studies, legal documents and files, as straightforward as product reviews. Data is more crucial than ever before; businesses spend a lot of money trying to gain as much insight as they can. Text and document data being more plentiful than other types of data and therefore, innovative methods to utilize the data are required. Because data is unstructured and abundant, arranging data in a digestible manner can significantly increase the value of data. Utilizing Text Classification with Machine Learning can be able to automatically organize relevant texts in a more efficient and more cost-effective method. We will discuss the concept of the term "text classification," explain the way it fun

What is training data for machine learning? Introduction Machine learning algorithms are one of the most interesting technologies around. They solve problems without any need for specific instructions. Machine learning algorithms need a lot of data in order to function. It is difficult to pinpoint the reasons why an algorithm performs poorly when it has millions, or even trillions, of photos and records. A flawed data gathering process can make machine learning useless or even harmful, regardless of the amount of data available and the data science talent. The problem is that it is very unlikely that an ideal dataset exists. There are several things companies can do to ensure their data science and machine learning efforts produce the best possible outcomes. What is a Training Dataset? To be able to use the AI Training Dataset as a starting point for other artificial intelligence algorithms and neural networks, it is essential that you have a data set. This dataset is the base for the