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The new words and Phrases from uploaded articles...
10 Computer Vision terms
The summary of 6 weeks. English Toolkit Course Skoltech
- Artificial intelligence; Unobtrusive; Medical diagnostics; Database; Facial recognition.
- Week 4
- Artificial intelligence - the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages; Unobtrusive - not conspicuous or attracting attention; Medical diagnostics - medical diagnosis is the process of determining which disease or condition explains a person's symptoms and signs; Database - a structured set of data held in a computer, especially one that is accessible in various ways; Facial recognition - technology that makes it possible for a computer to recognize a digital image of someone's face;
- Example: The first step would be designing a new app which takes advantage of artificial intelligence. Camera-based methods offer an unobtrusive solution for the monitoring and diagnosis of subjects. Thus, the detection of facial abnormalities or atypical features is at upmost importance when it comes to medical diagnostics. Furthermore, future perspectives, such as the need for interdisciplinary collaboration and collecting publicly available databases, are highlighted. A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces, typically employed to authenticate users through ID verification services, works by pinpointing and measuring facial features from a given image.
- en: Artificial intelligence - Искусственный интеллект; Unobtrusive - Ненавязчивый; Medical diagnostics - Медицинская диагностика; Database - База данных; Facial recognition - Распознавание лиц.
- Digital
- Adjective
- Digital - recording or storing information as a series of the numbers 1 and 0, to show that a signal is present or absent.
- Example: The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data from our cities.
- en: Digital - Цифровой
- Framework;
Neuron;
Dataset;
Regression;
Indicator.
- Week 6
- Framework - an essential supporting structure of a building, vehicle, or object.;
Neurons - are the fundamental units of the brain and nervous system, the cells responsible for receiving sensory input from the external world;
Dataset - a collection of related sets of information that is composed of separate elements but can be manipulated as a unit by a computer.;
Regression - a measure of the relation between the mean value of one variable (e.g. output) and corresponding values of other variables (e.g. time and cost).;
Indicator - a thing that indicates the state or level of something.
- Example: Second, with the preprocessing for unstructured data, a wide range of problems can be compatible with
deep learning frameworks.In the hidden layers, each neuron has dense connections with all the outputs from the previous layer.We can improve time efficiency on training models through parallel computing by GPU-based implementation in terms of the size of datasets and complexity of model structures.The network is trained to fit the training dataset by seeking the minimum of a parameterized loss function. In regression problems, the loss function is often defined as the mean square error (MSE). We use test loss as an indicator
to evaluate the effectiveness of the model.
- en: Framework - Каркас;
Neuron - Нейрон;
Dataset - Набор данных;
Regression - Регрессия;
Indicator - Индикатор.
- Large-scale
- Adjective
- Large-scale - involving large numbers or a large area; extensive.
- Example: The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data from our cities.
- en: Large-scale - Крупномасштабные
- Machine learning; Data science; Feature; Data analysis; Digitalisation.
- Week 2
- Machine learning - the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data; Data science - data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data; Feature - a distinctive attribute or aspect of something; Data analysis - data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making; Digitalisation - the conversion of text, pictures, or sound into a digital form that can be processed by a computer.
- Example: By employing data science and machine learning techniques, we identify the main features observed by the citizens through both text and images. It was earlier mentioned that the app did not produce some expected result for the data analysis, with only 418 observations being recorded at the time of the observation.The advancements in technology and the digitalisation of the physical world, allows the Internet of Things (IoT) to encourage a variety of multidisciplinary studies.
- en: Machine learning - Машинное обучение; Data science - Наука о данных; Feature - Характеристика; Data analysis - Анализ данных; Digitalisation - Цифровизация.
- Objective
- Adjective
- Objective - not influenced by personal feelings or opinions in considering and representing facts.
- Example: With the help of a smartphone app, both objective and subjective data were collected.
- en: Objective - Объективные
- Paradigm; Deep neural network; Sensor; Variables; Prototype.
- Week 5
- Paradigm - a typical example or pattern of something; a pattern or model.; Deep neural network - a deep neural network is a neural network with a certain level of complexity, a neural network with more than two layers; Sensor - a device which detects or measures a physical property and records, indicates, or otherwise responds to it; Variables - a data item that may take on more than one value during the runtime of a program.; Prototype - a basic filter network with specified cut-off frequencies, from which other networks may be derived to obtain sharper cut-offs, constancy of characteristic impedance with frequency, etc.;
- Example: To implement the new paradigm in a data-driven way, we adopt a fundamental fully-connected (FC) neural network as the basic framework.We used deep neural network as a predictive tool to explore sophisticated non-linear relationships between input features and target variables.This obviously discourages regular use because the sensors can be uncomfortable or encumbering. Although the data sources and the model structures we implemented were limited, we still believe that such a prototype training process can provide insights on designing a similar system to the research community.
- en: Paradigm - Парадигма; Deep neural network - Глубокая нейронная сеть; Sensor - Сенсор; Variables - Переменные; Prototype - Прототип;
- Social science; Smart Cities; Urban analytics; Big data; Classification.
- Week 3
- Social science - the scientific study of human society and social relationships; Smart Cities - smart city uses information and communication technology (ICT) to improve operational efficiency, share information with the public and provide a better quality of government service and citizen welfare; Urban analytics - methods of mathematical and symbolic modelling that generate insights into existing data as well as predictions of future data; Big data - extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions; Classification - the action or process of classifying something.
- Example: Through the use of technology, particularly smartphones, we aim at complementing the traditional way of gathering data in social sciences. While such objective studies may perform better at collecting information faster and at a larger scale, they hardly account for the harmonious interac tion between these smart objects and the humans, an important element in smart cities.The urban analytics programme at the Turing is focused on the process, structure, interactions and evolution of agents, technology and infrastructure within and between cities across spatial and temporal scales.Most definitions and studies of Big Data in cities are limited by the volume attribute of Big Data. Location was not taken into account here as the focus was rather on classification and feature extraction.
- en: Social science - Социальные науки; Smart Cities - Умные города; Urban analytics - Городская аналитика; Big data - Большие данные; Classification - Классификация.
- Subjective.
- Adjective
- Subjective - based on or influenced by personal feelings, tastes, or opinions.
- Example: With the help of a smartphone app, both objective and subjective data were collected.
- en: Subjective - Субъективные
- Technology
- Noun
- Technology - the application of scientific knowledge for practical purposes, especially in industry. "advances in computer technology".
- Example: The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data from our cities.
- en: Technology - Технология