The development of artificial intelligence is becoming more and more noticeable every year on many levels in organizations. The use of modern technology significantly affects the provision of security and better management of confidential data.
Image Classification technology, through the use of advanced deep learning algorithms, is able to analyze and recognize images, even those that potentially contain sensitive data.
Image classification – what is it?
Image Classification is the analysis of images based on their actual content. The goal of this process is to assign all pixels to one of many predefined classes. Identification of individual image features assigns the image to the appropriate representation. The deep learning (DL) technology implemented in the classification process allows categorization to be performed with very high efficiency.
How does it work?
By using deep learning, images are classified with high accuracy and speed. The operation of deep learning technology often uses the CNN (Convolutional neural network) method, which provides high efficiency and effectiveness in performing classification. The process of image recognition also often involves the concept of computer vision, which, however, does not cope as well with the analysis of images as when using a method using neural networks. Computer vision accurately classifies images only when there is no noise and interference in the data provided. With the CNN method, the classifier is able to effectively detect objects in the image, recognize the face, and understand the context. To ensure the best performance of this method, it is important that the provided data from which the artificial intelligence model will be created is of the highest possible quality.
Convolutional neural network
Convolutional neural network is a term for deep neural network architecture. The essence of its operation is to classify individual pixels and increase the number of pixels as the network passes through successive layers. The analysis of pixels increases proportionally from 1×1 pixel to 2×2, successively to 4×4. The following graphic shows the classification process of passing through successive layers of the image.
CNN, or convolutional neural network, is considered one of the more effective methods in image classification. Convolutional neural network provides a broader view of the process. The method analyzes an image by considering its context. An important consideration when using the CNN method for image classification is to ensure that the number of graphics for each category is similar or the same, to avoid the phenomenon where the trained convolutional neural network will be unbalanced.
Recognizing and hiding sensitive data
Image classification through deep learning technology, as well as the use of the convolutional neural network method, creates the possibility of categorization with very high efficiency. With this comes the possibility of recognizing sensitive data, which increases the level of security. Thanks to the analysis and interpretation, it is possible to block the sending of images containing sensitive data, such as document scans or identity documents outside the organization. The algorithm detects sensitive information placed on the graphic and hides it accordingly, such as by blurring. The image classifier is a key solution for securing organizations and protecting sensitive data.
BTC Deep Learning Image Classification
BTC Deep Learning Image Classification provides effective image classification by using deep learning technology. Using advanced algorithms, images are analyzed with very high accuracy. Classification is performed by category (26 categories), as well as subcategory (1083 subcategories), which significantly affects the efficient and effective operation of the classifier. The algorithms used accurately define the objects in the image, categorizing them accordingly. BTC Deep Learning Image Classification enables classification both on the basis of the URL of the analyzed image and by loading the file. In addition, the classifier is characterized by high speed, with categorization taking about 0.1 seconds. By using convolutional neural networks, the classifier is able to effectively secure the organization by identifying and securing sensitive data.
Source
www.kdnuggets.com/2016/11/intuitive-explanation-convolutional-neural-networks.html/3