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An ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it a…

  • Updated Nov 15, 2023

SQL Injection attack is the most common website hacking technique. Most websites use Structured Query Language (SQL) to interact with databases. SQL allows the website to create, retrieve, update, and delete database records. It used for everything from logging a user into the website to storing details of an eCommerce transaction. An SQL inject…

  • Updated Jul 16, 2022

A denial of service attack floods a website with a huge amount of Internet traffic, causing its servers to become overwhelmed and crash. Most DDoS attacks are carried out using computers that have been compromised with malware. The owners of infected computers may not even be aware that their machine is sending requests for data to your website.…

  • Updated Dec 14, 2021

In developmental robotics, robot learning algorithms generate their own sequences of learning experiences, also known as a curriculum, to cumulatively acquire new skills through self-guided exploration and social interaction with humans. These robots use guidance mechanisms such as active learning, maturation, motor synergies and imitation. Asso…

  • Updated Nov 7, 2020

In some cases, the greatest weakness in a website’s security system is the people that use it. Social engineering seeks to exploit this weakness. A hacker will convince a website user or administrator to divulge some useful information that helps them exploit the website. There are many forms of social engineering attacks, including: Phishing Us…

  • Updated Jan 7, 2021

In many cases, hackers won’t specifically target your website. They will be targeting a vulnerability that exists for a content management system, plugin, or template. For example, they may have developed a hack that targets a vulnerability in a particular version of WordPress, Joomla, or another content management system. They will use automate…

  • Updated Jan 7, 2021

The classical problem in computer vision, image processing, and machine vision is that of determining whether or not the image data contains some specific object, feature, or activity. Different varieties of the recognition problem are described in the literature:[citation needed] Object recognition (also called object classification) – one or s…

  • Updated Dec 28, 2020

This hacking technique injects corrupt domain system data into a DNS resolver’s cache to redirect where a website’s traffic is sent. It is often used to send traffic from legitimate websites to malicious websites that contain malware. DNS spoofing can also be used to gather information about the traffic being diverted. The best techniques for pr…

  • Updated Jan 7, 2021

Self-learning as a machine learning paradigm was introduced in 1982 along with a neural network capable of self-learning named crossbar adaptive array (CAA).[44] It is a learning with no external rewards and no external teacher advice. The CAA self-learning algorithm computes, in a crossbar fashion, both decisions about actions and emotions (fee…

  • Updated Nov 7, 2020

Reinforcement learning is an area of machine learning concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. Due to its generality, the field is studied in many other disciplines, such as game theory, control theory, operations research, information theory, simulation-based …

  • Updated Nov 7, 2020

A second application area in computer vision is in industry, sometimes called machine vision, where information is extracted for the purpose of supporting a manufacturing process. One example is quality control where details or final products are being automatically inspected in order to find defects. Another example is measurement of position a…

  • Updated Dec 28, 2020

Supervised learning algorithms build a mathematical model of a set of data that contains both the inputs and the desired outputs.[38] The data is known as training data, and consists of a set of training examples. Each training example has one or more inputs and the desired output, also known as a supervisory signal. In the mathematical model, e…

  • Updated Nov 7, 2020

One of the newer application areas is autonomous vehicles, which include submersibles, land-based vehicles (small robots with wheels, cars or trucks), aerial vehicles, and unmanned aerial vehicles (UAV). The level of autonomy ranges from fully autonomous (unmanned) vehicles to vehicles where computer-vision-based systems support a driver or a pi…

  • Updated Jan 18, 2023

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