A new study led by the University of Exeter and the Center for Whale Research suggests killer whales may socialise with each other based on age and gender, with younger whales and females more sociable than other groups. The research used drone cameras to study one pod of southern resident killer whales off the US coast of Washington State, in the Pacific Ocean. Around 10 hours of footage was captured over 10 days.
There are now two ways of creating digital images with a camera. You can either follow a software-centric computational photography approach. The other way is to stick to traditional hardware-centric optical photography. The former is used with AI to help enhance the final image, the latter relies on the quality of the camera's components (e.g. The two techniques may differ, but they are not at all on a collision course.
This summer, the whole world watched in horror as thousands of fires, again this year, ravaged the Amazon rainforest. Yet the forests are specific ecosystems: they are carbon sinks, meaning they stock carbon dioxide outside of the atmosphere; their destruction is contributing to climate change. To fight this phenomenon and protect the environment, governments, associations, scientists and local communities are relying more and more on technological advances. More specifically, here's how satellite imagery, artificial intelligence, and drones are being deployed in environmental battles. Combined with other sources of information (data collected in the field, aerial photography, etc.), satellite imagery makes it possible to analyse the evolution of forests, to detect changes that have arisen in a particular area and over a given period of time, and, ultimately, to determine the rate of global deforestation.
Wouldn't it be convenient if you could see who's outside your door before you even open it? With the Wireless IP 1081P Smart Video Camera Doorbell, you can get the security and mental freedom you're looking for. It connects to your home WiFi and transmits a real-time video feed to your phone, tablet, or another device of your choice. You'll receive alerts any time movement is detected, thanks to built-in motion sensors, as well as a crisp, high-quality photo. It's even equipped with night vision, so you'll be able to see what's going on in the dark. With its built-in dual speakers, you'll be able to communicate with whoever is at the door as well.
China's space agency has released the first photos taken by the Zhurong rover on Mars, showing parts of its lander and the red planet itself. The Tianwen-1 mission arrived at its destination on May 15th, making China the second nation to successfully soft-land on Mars after the US. One of the photos is a colored image (above) taken by the navigation camera mounted at the rear of the rover. It features Zhurong's solar panels and unfolded antennae, along with a view of the planet's red soil and rocks. The other photo (below) is a black-and-white image taken by an obstacle avoidance camera installed in front of the rover. It was captured using a wide-angle lens, so it not only shows a ramp from the lander extending to the surface of the planet, but also the Martian horizon.
Every day, billions of photos and videos are posted to various social media applications. The problem with standard images taken by a smartphone or digital camera is that they only capture a scene from a specific point of view. But looking at it in reality, we can move around and observe it from different viewpoints. Computer scientists are working to provide an immersive experience for the users that would allow them to observe a scene from different viewpoints, but it requires specialized camera equipment that is not readily accessible to the average person. To make the process easier, Dr. Nima Kalantari, professor in the Department of Computer Science and Engineering at Texas A&M University, and graduate student Qinbo Li have developed a machine-learning-based approach that would allow users to take a single photo and use it to generate novel views of the scene.
First we had deepfakes, which could glue someone's face onto someone else's body. Then we had This Person Does Not Exist, which created people on a website every time you refreshed the page. Then we had Generated Photos, a commercial stock photography site, built entirely from AI-generated humans. Generating realistic-looking people has been one of the biggest challenges in visual AI, but researchers are mastering the technique quickly. The latest example: Generated Photos--which currently does $15,000 a month in revenue selling a library of AI-generated stock models, according to the company--has released an update that not only generates an AI-built human on demand but also lets you position it.
Have you interacted with a digital persona yet? At the Museum of Art & Photography in Bangalore, you can have a deep and engaging exchange with one that represents the late artist M.F. Husain -- considered the "Picasso of India" by many. This avatar is eager to talk art. And if you ask him whether he's real, he will look straight at you and say, "As close to real, enough to impress you."
China's Vivo has a new photography-centered smartphone, with a twist: while the rear camera is quite powerful as well, the front (selfie) camera is where Vivo threw everything and the kitchen sink. The Vivo V21 -- which comes in two flavors, Vivo V21 and Vivo V21 5G -- has a 44-megapixel self camera with optical image stabilization, electronic image stabilization, and autofocus, all of which should help produce some pretty awesome selfies. There's also a "groundbreaking" light sensor helping selfies look better according to Vivo, though the company shared no details about that. The front camera also supports 4K video recording, and has a feature called the AI Night Portrait, which uses AI to reduce noise in dark environments, which (again) should result in high quality selfies, even at night. The rest of the specs are pretty sweet as well, though some costs have definitely been cut compared to your typical flagship phone.
Researchers at UniSA have developed a cost-effective new technique to monitor soil moisture using a standard digital camera and machine learning technology. The United Nations predicts that by 2050 many areas of the planet may not have enough fresh water to meet the demands of agriculture if we continue our current patterns of use. One solution to this global dilemma is the development of more efficient irrigation, central to which is precision monitoring of soil moisture, allowing sensors to guide'smart' irrigation systems to ensure water is applied at the optimum time and rate. Current methods for sensing soil moisture are problematic – buried sensors are susceptible to salts in the substrate and require specialised hardware for connections, while thermal imaging cameras are expensive and can be compromised by climatic conditions such as sunlight intensity, fog, and clouds. Researchers from The University of South Australia and Baghdad's Middle Technical University have developed a cost-effective alternative that may make precision soil monitoring simple and affordable in almost any circumstance.