"What exactly is computer vision then? Computer vision is a research field working to equip computers with the ability to process and understand visual data, as sighted humans can. Human brains process the gigabytes of data passing through our eyes every second and translate that data into sight - that is, into discrete objects and entities we can recognise or understand. Similarly, computer vision aims to give computers the ability to understand what they are seeing, and act intelligently on that knowledge."
– Computer vision: Cheat Sheet. ZDNet.com (December 6, 2011), by Natasha Lomas.
As cases of violence against women and girls have surged in South Asia in recent years, authorities have introduced harsher penalties and expanded surveillance networks, including facial recognition systems, to prevent such crimes. Police in the north Indian city of Lucknow earlier this year said they would install cameras with emotion recognition technology to spot women being harassed, while in Pakistan, police have launched a mobile safety app after a gang rape. But use of these technologies with no evidence that they help reduce crime, and with no data protection laws, has raised alarm among privacy experts and women's rights activists who say the increased surveillance can hurt women even more. "The police does not even know if this technology works," said Roop Rekha Verma, a women's rights activist in Lucknow in Uttar Pradesh state, which had the highest number of reported crimes against women in India in 2019. "Our experience with the police does not give us the confidence that they will use the technology in an effective and empathetic manner. If it is not deployed properly, it can lead to even more harassment, including from the police," she said.
As artificial intelligence (AI) becomes more pervasive and embedded in life-changing decisions, the need for transparency has intensified. There have been plenty of high-profile cases in recent years where AI has contributed to bias and discrimination, with the use of facial recognition for policing just one example. There is a high probability of a shift from loose self-regulation to government involvement in AI over the next couple of years. In turn, Big Tech is increasingly using AI to solve the privacy and bias problems that the technology itself created. Listed below are the key technology trends impacting the AI theme, as identified by GlobalData.
Register for a free or VIP pass today. CrowdAI, a computer vision development platform, today announced that it closed a $6.25 million series A financing round led by Threshold Ventures. The fundraising coincides with the launch of the startup's new solution that allows customers to create AI that analyzes images and videos. The AI skills gap remains a significant impediment to adoption in most enterprises, a 2020 O'Reilly survey found. Slightly more than one-sixth of respondents cited difficulty in hiring experts as a barrier to AI deployment in their organizations.
The precision and promise of a data-driven society has stumbled these past years, serving up some disturbing--even damning--results: facial recognition software that can't recognize Black faces, human resource software that rejects women's job applications, talking computers that spit racist vitriol. "Those who don't learn history are doomed to repeat it," George Santayana said. But most artificial intelligence applications and data-driven tools learn history aplenty--they just don't avoid its pitfalls. Instead, though touted as a step toward the future, these systems generally learn the past in order to replicate it in the present, repeating historical failures with ruthless, and mindless, efficiency. As Joy Buolamwini says, when it comes to algorithmic decision-making, "data is destiny."
This article is about most probably the next generation of neural networks for all computer vision applications: The transformer architecture. You've certainly already heard about this architecture in the field of natural language processing, or NLP, mainly with GPT3 that made a lot of noise in 2020. Transformers can be used as a general-purpose backbone for many different applications and not only NLP. In a couple of minutes, you will know how the transformer architecture can be applied to computer vision with a new paper called the Swin Transformer by Ze Lio et al. from Microsoft Research . This article may be less flashy than usual as it doesn't really show the actual results of a precise application.
The vaccine rollout is being met with lifted COVID-19 restrictions inside buildings and restaurants, but this change presents a new challenge to business owners -- managing increased occupancy, while still abiding by safety restrictions. Businesses that find themselves exceeding occupancy could face fines, citations, and license suspensions. One increasingly prominent solution employs 3D counting and tracking cameras that monitor occupancy, foot traffic, and flow inside brick-and-motor locations. Regular 2D cameras and traditional counting techniques are not accurate enough. However, depth-sensing 3D cameras can provide real-time updates that increase counting accuracy by an estimated 5% to 8%, according to a spokesperson for one 3D company I spoke with, Orbbec.
Facial recognition is problematic for humans. When it works, it invades privacy and eases us into a surveillance state. When it doesn't work, people have been falsely arrested by police. For bears, it's all good – and facial recognition is now being used to help research, monitor and protect the animals using a neural network-based system called BearID. Normally, that requires methodically examining photographs or physically tagging the animal, as the University of Victoria researcher's work on grizzly behaviour requires being able to pinpoint a specific individual.
Pain felt by women is perceived as less intense by observers as pain felt by men, a new study reveals. US scientists found that when male and female patients experienced the same amount of pain, observers viewed female patients' pain as milder and more likely to benefit from psychotherapy than medication. Both male and female observers were found to be guilty of this'gender bias', which could lead to disparities in treatments and women in pain not getting the medication they need. According to the experts, the bias is due to an age-old stereotype that men are more'stoic' that women – and so their pain is likely to be more serious. University of Miami researchers found that when male and female patients expressed the same amount of pain, observers viewed female patients' pain as less intense and more likely to benefit from psychotherapy versus medication as compared to men's pain, exposing a significant patient gender bias that could lead to disparities in treatments (stock image) Health professionals use different terms for different types of pain.
Just a couple of months after Ring unwrapped its new, radar-enabled aerial view for the Video Doorbell Pro 2, the Amazon-owned smart brand is now rolling out the clever technology to its updated wired floodlight. At the same time, Ring says it's bringing a color version of its pre-roll video feature to a fourth generation of its battery-powered video doorbell. Slated to ship on May 6 for $250 (you can preorder starting today), the Ring Floodlight Cam Wired Pro will boast both Bird's-Eye View and 3D Motion Detection, a pair of features powered by radar rather than infrared motion sensors. Meanwhile, the Ring Video Doorbell 4 is set to arrive April 28 for $200, and it will add color to the pre-roll functionality that debuted on last year's Video Doorbell 3 Plus. An upgrade to 2019's well received Floodlight Cam, the revamped Floodlight Cam Wired Pro arrives with the same 1080p video resolution while adding HDR for a needed contrast boost, along with a 140-degree (horizontal) by 60-degree (vertical) field of view.
Identifying what someone is feeling or even anticipating potential reactions based on nonverbal behavioral cues is no longer a problem reserved for sensitive and astute people. With the advancement of cutting-edge technologies in emotional intelligence, this capability gains new dimensions with the capability of machines recognizing human emotions for a variety of purposes. Complex facial detection algorithms are now powerful enough to analyze and measure emotions captured in real-world situations. They are so powerful that we are reaching a point that some ethical aspects have been raised. Emotion Recognition is based on facial expression recognition, a computer-based technology that employs algorithms to detect faces, code facial expressions, and recognize emotional states in real-time.