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Sensing and Signal Processing


China and AI: What the World Can Learn and What It Should Be Wary of

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China announced in 2017 its ambition to become the world leader in artificial intelligence (AI) by 2030. While the US still leads in absolute terms, China appears to be making more rapid progress than either the US or the EU, and central and local government spending on AI in China is estimated to be in the tens of billions of dollars. The move has led--at least in the West--to warnings of a global AI arms race and concerns about the growing reach of China's authoritarian surveillance state. But treating China as a "villain" in this way is both overly simplistic and potentially costly. While there are undoubtedly aspects of the Chinese government's approach to AI that are highly concerning and rightly should be condemned, it's important that this does not cloud all analysis of China's AI innovation.


Automated histologic diagnosis of CNS tumors with machine learning

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A new mass discovered in the CNS is a common reason for referral to a neurosurgeon. CNS masses are typically discovered on MRI or computed tomography (CT) scans after a patient presents with new neurologic symptoms. Presenting symptoms depend on the location of the tumor and can include headaches, seizures, difficulty expressing or comprehending language, weakness affecting extremities, sensory changes, bowel or bladder dysfunction, gait and balance changes, vision changes, hearing loss and endocrine dysfunction. A mass in the CNS has a broad differential diagnosis, including tumor, infection, inflammatory or demyelinating process, infarct, hemorrhage, vascular malformation and radiation treatment effect. The most likely diagnoses can be narrowed based on patient demographics, medical history, imaging characteristics and adjunctive laboratory studies. However, accurate histopathologic interpretation of tissue obtained at the time of surgery is frequently required to make a diagnosis and guide intraoperative decision making. Over half of CNS tumors in adults are metastases from systemic cancer originating elsewhere in the body [1]. An estimated 9.6% of adults with lung cancer, melanoma, breast cancer, renal cell carcinoma and colorectal cancer have brain metastases [2].


What is Image Recognition their functions, algorithm and its uses

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The visual performance of Humans is much better than that of computers, probably because of superior high-level image understanding, contextual knowledge, and massively parallel processing. But human capabilities deteriorate drastically after an extended period of surveillance, also certain working environments are either inaccessible or too hazardous for human beings. So for these reasons, automatic recognition systems are developed for various applications. Driven by advances in computing capability and image processing technology, computer mimicry of human vision has recently gained ground in a number of practical applications. Image recognition refers to technologies that identify places, logos, people, objects, buildings, and several other variables in digital images.


How Google Might Rank Image Search Results - SEO by the Sea

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We are seeing more references to machine learning in how Google is ranking pages and other documents in search results. That seems to be a direction that will leave what we know as traditional, or old school signals that are referred to as ranking signals behind. It's still worth considering some of those older ranking signals because they may play a role in how things are ranked. As I was going through a new patent application from Google on ranking image search results, I decided that it was worth including what I used to look at when trying to rank images. Images can rank highly in image search, and they can also help pages that they appear upon rank higher in organic web results, because they can help make a page more relevant for the query terms that page may be optimized for.


Photo finish: Two new AI methods for improving quality of photographs

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The amount of visual data we accumulate around the world is mind boggling. However, not all the images are captured by high-end DSLR cameras, and very often they suffer from imperfections. It is of tremendous benefit to save those degraded images so that users can reuse them for their own design or other aesthetic purposes. In this blog, we are going to present our latest efforts in image enhancement. The first technique enhances the image resolution of an image file by referring to external reference images.


China and AI: what the world can learn and what it should be wary of

#artificialintelligence

China announced in 2017 its ambition to become the world leader in artificial intelligence (AI) by 2030. While the US still leads in absolute terms, China appears to be making more rapid progress than either the US or the EU, and central and local government spending on AI in China is estimated to be in the tens of billions of dollars. The move has led – at least in the West – to warnings of a global AI arms race and concerns about the growing reach of China's authoritarian surveillance state. But treating China as a "villain" in this way is both overly simplistic and potentially costly. While there are undoubtedly aspects of the Chinese government's approach to AI that are highly concerning and rightly should be condemned, it's important that this does not cloud all analysis of China's AI innovation.


China and AI: what the world can learn and what it should be wary of - IPE Club

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By Hessi Elliot /The Conversation/ – China announced in 2017 its ambition to become the world leader in artificial intelligence (AI) by 2030. While the US still leads in absolute terms, China appears to be making more rapid progress than either the US or the EU, and central and local government spending on AI in China is estimated to be in the tens of billions of dollars. The move has led – at least in the West – to warnings of a global AI arms race and concerns about the growing reach of China's authoritarian surveillance state. But treating China as a "villain" in this way is both overly simplistic and potentially costly. While there are undoubtedly aspects of the Chinese government's approach to AI that are highly concerning and rightly should be condemned, it's important that this does not cloud all analysis of China's AI innovation.


Top 10 Processor to Watch in 2020 - Analytics Insight

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The Internet of Things (IoT) has sparked the proliferation of connected devices. These devices, which house sensors to collect data of the day-to-day activities or monitoring purposes, are embedded with microcontrollers and microprocessors chips. These chips are mounted based on the data sensor needed to complete an assigned task. So we don't have a one processor fits all architecture. For example, some devices will perform a limited amount of processing on data sets such as temperature, humidity, pressure, or gravity; more complicated systems, however, will need to handle (multiple) high-resolution sound or video streams.


Disney's Developed Movie-Quality Face-Swapping Technology That Promises to Change Filmmaking

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In a few short years, neural-network-powered automated face swaps have gone from being mildly convincing to eerily believable. But through new research from Disney, neural face-swapping is poised to become a legitimate and high-quality tool for visual effects studios working on Hollywood blockbusters. One of the bigger challenges of creating deepfake videos, as they've come to be known, is creating a vast database of facial images of a person--thousands of different expressions and poses--that can be swapped into a target video. The larger the database and the higher the quality of the images, the better the face swaps will turn out. But the images (which are more often than not headshots of famous people) are usually pulled from sources with limited resolution.


How Machine Learning Can Improve the Efficiency of Fuel Cells?

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The world is adapting itself to the digital age changes. We are getting more familiar with the terms of the disruptive technologies that are making it happen. Internet of things (IoT) is one of them. The term was coined by in 1999 by Kevin Ashton, a British technologist. It refers to the connected ecosystem of devices and gadgets, which is benefiting businesses and industries of all types. These devices can be RFID chips, smart devices, or mobile sensors.