How GPT-3, your smartphone and Augmented Reality can disrupt a dinosaur industry. The earliest photographic studios made use of painters' lighting techniques to create portraits. In my country, generations of Indians would assemble under the studio lights to get that perfect family portrait. We have come a staggering distance since then. Today, these photo studios that were responsible for many families and their portraits, have all but disappeared.
After leaving Google in March, Marc Levoy, the imaging expert who helped create some of the Pixel lineup's most important computational photography features, has landed at Adobe. In an email, the Photoshop-maker said Levoy will "spearhead company-wide technology initiatives focused on computational photography and emerging products, centered on the concept of a universal camera app." Precisely what that universal camera app will entail Adobe hasn't said yet. However, the company notes Levoy will work with its Photoshop Camera, Adobe Research, Sensei and Digital Imaging teams. As The Verge notes, Adobe's Photoshop Camera and Lightroom apps already include camera functionality.
Kodak was a huge company, but after it declared bankruptcy in 2012, the company has faded dramatically. The rapid decline in demand for its core products (read: film vs. digital photography) decimated its market, leaving the company in an untenable position--even though Kodak invented the consumer digital camera, it failed to realize how quickly that technology would catch on. Kodak seemed like one of those companies that would always be here. Staying relevant has really turned out to be a challenge.
One of the big joys of "Umurangi Generation" is the sensation of seeing a scene in the game, and having the mirage of a perfect picture appear in your mind, if only for a second. It's impossible (at least for a photographer of my caliber) to visualize and capture it as-imagined, which opens up a second game within the game: one of curation. A no-less-enjoyable part of my "Umurangi" experience was scouring my file folder (the game saves all of your shots) after completing a level and being both repulsed and pleasantly surprised by what I'd created. The game reveals certain things about your aesthetic priorities. I preferred vertical images to horizontal ones, and I leaned toward overexposure and a blue tint in many of my photos, mirroring a sort of mid-2010s Bloomberg Businessweek aesthetic.
DJI's new Mavic Air 2 folding-style drone is a huge improvement over the previous model--so much so that for most people, this is the perfect drone. The Mavic Air 2 is the middle child in DJI's consumer drone lineup, sitting between the smaller, lighter, but less capable Mavic Mini, and the more powerful, more capable, but also more expensive, Mavic 2. If you're just getting started with drones, the less expensive Mavic Mini (8/10 WIRED Recommends)--my previous top pick for most people--might be a better buy. That said, the Air 2 offers better collision avoidance systems, higher quality photos and video, and a wide assortment of automated flight features that newcomers and seasoned vets alike can appreciate. The Mavic Air 2 is slightly bigger than its predecessor, at least on paper. The folding design remains compact, and at 1.3 pounds, the drone is plenty portable.
A new Artificial Intelligence (AI) algorithm, developed by scientists at the University of Hong Kong, can only create enormously realistic photos from sketch drawings. Researchers say the new algorithm can be used to identify suspects in police investigations. Despite the concerns of names like Tesla and SpaceX CEO Elon Musk, Artificial Intelligence (AI) technologies continue to penetrate every aspect of our lives. AI, which has a place in many sectors including security, health, military, automotive and transportation, is becoming more and more powerful. According to the information reported by the website of New Scientist, Hongbo Fu and colleagues from the University of Hong Kong developed an algorithm that can instantly convert a very simple sketch drawing representing the face of a person into portrait photography.
This article presents the development process of a Machine Learning model to gain understanding from Digital Magnetic Resonance Images (MRI) of the Human Knee and label the corresponding pixels of the image to the Tibia bone, using a Deep Learning network and image segmentation. Deep Convolutional networks have outperformed the state of the art in many visual recognition tasks, the image semantic segmentation challenge consists in classifying each pixel of an image into an instance corresponding to an object or a part of the image. The data set used, consisting of a total of 90 cases of the Human knee medical images, also known as Magnetic resonance Imaging MRI. Each case consists of a set of 160 medical images of the knee in format type Digital Imaging and Communications in Medicine or DICOM. In order to extract the area of interest in each DICOM image, the Tibia bone was labeled with a software called BML BaseLine, this software is used to mark the bounds of the bone on each DICOM image for each case.
Sony Corp. and Microsoft Corp. have partnered to embed artificial intelligence capabilities into the Japanese company's latest imaging chip, a big boost for a camera product the electronics giant describes as a world first for commercial customers. The new module's big advantage is that it has its own processor and memory built in, which allows it to analyze video using AI tech like Microsoft's Azure, but in a self-contained system that's faster, simpler and more secure to operate than existing methods. The two companies are appealing to retail and logistics businesses with potential uses like optimizing warehouse and factory automation, quantifying the flow of customers through stores and making cars smarter about their drivers and environment. At a time of increasing public surveillance to help rein in the spread of the coronavirus, this new smart camera also has the potential to offer more privacy-conscious monitoring. And should its technology be adapted for personal devices, it even holds promise for advancing mobile photography.
Sony has shown off what it's calling "the world's first image sensors to be equipped with AI processing functionality." These new sensors handle AI image analysis on board, so only the necessary data can be sent for further cloud processing. Artificial Intelligence is a natural pair with digital video cameras. They take in monstrous amounts of data, the vast majority of which is of no interest to anybody, particularly when you're talking about things like security cameras. As automation continues to escalate, we're going to need AI to keep an eye on more and more camera feeds.
Up Your Game: The Mavic Air 2 camera drone takes power and portability to the next level. It combines a powerful camera with intelligent shooting modes for stunning results. Push your imagination to its limits because aerial photography has never been this easy. Next-Level Content: Capture impressive 48MP photos with a 1/2-inch CMOS sensor while the 3-axis gimbal provides 4K/60fps video. The secret to incredible HDR video is a high-performance Quad Bayer image sensor.