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How To Build A Computer Vision Model Using AutoML


Are you thinking of learning programming languages like C, Python or R to work on machine learning projects? AutoML could save you all the time and effort. Lately, Automated machine learning or AutoML has become a popular solution to build computer vision systems. The tech communities are awash with conversations around AutoML as to how it will change the way machine learning is done with limited or no coding knowledge. From autonomous vehicles to handwritten text recognition, face recognition, personalised recommendations, and diagnosing from x-ray images, computer vision is transforming industries globally.

How Machine Learning is Beneficial to the Police Departments?


It is important to understand the basic nature of machines like computers in order to understand what machine learning is. Computers are devices that follow instructions, and machine learning brings in an interesting outlook, where a computer can learn from the experience without the need for programming. Machine learning transports computers to another level where they can learn intuitively in a similar manner as humans. It has several applications, including virtual assistants, predictive traffic systems, surveillance systems, face recognition, spam, malware filtering, fraud detection, and so on. The police can utilize machine learning effectively to resolve the challenges that they face.

Understanding the differences between biological and computer vision


Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence. Since the early years of artificial intelligence, scientists have dreamed of creating computers that can "see" the world. As vision plays a key role in many things we do every day, cracking the code of computer vision seemed to be one of the major steps toward developing artificial general intelligence. But like many other goals in AI, computer vision has proven to be easier said than done. In 1966, scientists at MIT launched "The Summer Vision Project," a two-month effort to create a computer system that could identify objects and background areas in images.

'Coded Bias' Film Explores How Artificial Intelligence Perpetuates Discrimination


Shalini Kantayya describes herself as a filmmaker who's fascinated with disruptive technologies and the good or harm they create. In a data-driven and increasingly automated world, there's a question of how to protect our civil liberties as artificial intelligence grows by the day. MIT researcher Joy Buolamwini discovered that most facial recognition technology does not see dark-skinned faces and women's faces accurately. This led to an investigation of how the technology we typically see as objective can actually encode racism and sexism. Buolamwini, and others working to change technology for the better around the globe, are featured in Kantayya's documentary Coded Bias.

EETimes - Embedded Vision at the Tipping Point


A technology reaches a tipping point when it hits three milestones: First, it becomes technically feasible to accomplish important tasks with it. Second, it becomes cheap enough to use for those tasks. And third, critically, it becomes sufficiently easy for non-experts to build products with it. Passing those milestones is a great indicator that a technology is poised to spread like wildfire. At this year's Embedded Vision Summit (coming up online May 25-28), we're seeing clear evidence that embedded vision has reached this point.

Massachusetts Pioneers Rules For Police Use Of Facial Recognition Tech

NPR Technology

Surveillance cameras, like the one here in Boston, are used throughout Massachusetts. The state now regulates how police use facial recognition technology. Surveillance cameras, like the one here in Boston, are used throughout Massachusetts. The state now regulates how police use facial recognition technology. Massachusetts lawmakers passed one of the first state-wide restrictions of facial recognition as part of a sweeping police reform law.

Automate visual recognition model training


This code pattern is part of the Getting started with IBM Maximo Visual Inspection learning path. Training a visual recognition model can be repetitive and tedious. Users generally have to manually upload and label each individual image. This code pattern shows how to automate these repetitive tasks by monitoring a set of folders using a Python script. As images are added to each folder, they'll be uploaded and labeled in IBM Maximo Visual Inspection.

A Universal Facial ID 'Master Key' Through Machine Learning


Italian researchers have developed a method by which it's possible to bypass facial recognition ID checks for any user, in systems that have been trained on a Deep Neural Network (DNN). The approach works even for target users that enrolled into the system after the DNN was trained, and potentially enables the providers of end-to-end encrypted systems to unlock the data of any user via facial ID authentication, even in scenarios where that is not supposed to be possible. The paper, from the Department of Information Engineering and Mathematics at the University of Siena, outlines a possible compromising of user-encrypted facial ID verification systems by introducing'poisoned' facial images into the training data sets that power them. Once introduced into the training set, the owner of the poisoned face is able to unlock the account of any user through facial ID authentication. Images used in the'Master Key' system, to be included at the training phase.

Computer Vision: How Machines Interpret the Visual World


Computer vision (CV) is a field of artificial intelligence that strives to develop techniques that enable computers to see and understand the content of digital images. In other words, computer vision attempts to train machines to see and comprehend the world around them.

Easily copy and paste text from images with this clever Mac app


TL;DR: A lifetime subscription to TextSniper for Mac is on sale for £2.87 as of May 7, saving you 42% on list price. TextSniper is a Mac app that lets you extract text from sources like images, YouTube videos, PDFs, screenshots, or presentations. Thanks to advanced OCR (optical character recognition) technology, TextSniper can scan and recognise the text within any digital image, video, or document. It will then copy it, allowing you to paste the text directly into an editable format, like a note, text, or even Google Doc. It can also turn recognized text into speech, in case there's a word or phrase you need to be pronounced, and scan barcodes and QR codes and turn them into text. SEE ALSO: Want to unblock American Netflix from the UK? Try this speedy VPN.