Pattern Recognition


Can artificial intelligence and IoT feed the planet's growing population?

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The innovation behind these transformations is machine learning, a kind of algorithm that ingests and analyzes tons of data to find common patterns, and turn those patterns into predictions and actions. The practice, known as "precision farming," uses real-time and historical data along with machine learning algorithms to take specific actions for smaller areas and time increments instead of performing the same thing for a very large area in a routine-based manner. Deep learning and computer vision algorithms analyze the collected data to learn and report when something important is happening. These tasks can be as easy as controlling irrigation on different parts of the field based on humidity data obtained from sensors, or notifying distribution partners based on the amount and time of yield expected.


Can artificial intelligence and IoT feed the planet's growing population?

#artificialintelligence

The innovation behind these transformations is machine learning, a kind of algorithm that ingests and analyzes tons of data to find common patterns, and turn those patterns into predictions and actions. The practice, known as "precision farming," uses real-time and historical data along with machine learning algorithms to take specific actions for smaller areas and time increments instead of performing the same thing for a very large area in a routine-based manner. Deep learning and computer vision algorithms analyze the collected data to learn and report when something important is happening. These tasks can be as easy as controlling irrigation on different parts of the field based on humidity data obtained from sensors, or notifying distribution partners based on the amount and time of yield expected.


Possible Applications of AI in HR Hppy

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HR management personnel work with the latest HR tools to track a candidate's journey through the interview process. Smart badges collect relevant information such as dialogues between employees, networks in the company, where people spend their time, interactions, etc. New technology enables HR professional to measure things like effectiveness, efficiency, and employee experience by analyzing hiring decisions, personal development, and overall team climate. Although some HR departments utilize AI in their decision making processes, the technology still needs to be developed to the full extent.


Machine Learning and Medical Imaging (Elsevier and Micca Society): Guorong Wu, Dinggang Shen, Mert Sabuncu: 9780128040768: Amazon.com: Books

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Guorong Wu is an Assistant Professor of Radiology and Biomedical Research Imaging Center (BRIC) in the University of North Carolina at Chapel Hill. Dr. Wu's research aims to develop computational tools for biomedical imaging analysis and computer assisted diagnosis. Dinggang Shen is a Professor of Radiology, Biomedical Research Imaging Center (BRIC), Computer Science, and Biomedical Engineering in the University of North Carolina at Chapel Hill (UNC-CH). Dr. Shen's research interests include medical image analysis, computer vision, and pattern recognition.


Co-Clustering Can Provide Industrial Data Pattern Discovery

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Data clustering is the classification of data objects into different groups (clusters) such that data objects in one group are similar together and dissimilar from another group. Collaborative information filtering applications such as movie recommender systems co-cluster the accumulated movie rating provided by viewers and the movies they have watched. Using this information, the viewer is recommended other movies by classifying the rating he/she provided to a viewer ratings-movies watched cluster. An entry Cij of the matrix signifies the relation between the data type represented by row i and column j. Co-clustering is the problem of deriving sub-matrices from the larger data matrix by simultaneously clustering rows and columns of the data matrix.


How logic games have advanced AI thinking

@machinelearnbot

Raymond Bird, the electronics engineer who was tasked with developing the HEC, described the demonstration of the noughts and crosses game as a great success in showing the potential power of computers. It led to the development of expert systems – machines that could become domain experts in areas such as medical diagnosis, says Herbert. With ubiquitous internet access, much more data became available, which led to what is now called machine learning. A big driver was search engine development by the likes of Bing, Google and AltaVista and, later, the recommendation engines – all of which are based on pattern recognition technology.


Artificial intelligence can identify 'gay faces' from a picture, study claims

The Independent

According to its authors, who say they were "really disturbed" by their findings, the accuracy of an AI system can reach 91 per cent for homosexual men and 83 per cent for homosexual women. The paper, titled Deep neural networks are more accurate than humans at detecting sexual orientation from facial images, was co-authored by Stanford University's Yilun Wang and Michal Kosinski, and first spotted by the Economist. The researchers say that homosexual men were found to have narrower jaws, longer noses, larger foreheads and less facial hair than heterosexual men, and that homosexual women tended to have larger jaws and smaller foreheads than heterosexual women. "Additionally, consistent with the association between baseball caps and masculinity in American culture, heterosexual men and lesbians tended to wear baseball caps."


Valencia AI Applied Artificial Intelligence Community

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Dr. Roberto Paredes joined in 2000 the Computer Science Department of the Universidad Politécnica de Valencia (UPV), where he is until now serving as an Associate Professor. His current fields of interest include Statistical Pattern Recognition, Machine Learning, Biometrics, Large-scale problems, Multimedia Retrieval and Relevance Feedback. Moreover he is now the CTO and Co-founder of Solver Machine Learning, a spin-off of the UPV. Nowadays he is focused mainly in Deep Learning techniques and some of his DL solutions are applied to different sectors where Solver Machine Learning is working on.


Responding to Bad Restaurant Reviews – Be Proactive

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While the marketing function should own the task of monitoring, analyzing and responding to social media commentary, close collaboration with IT is imperative. By combining technology tools and clearly defined processes around incident response, innovative restaurant chains are developing proactive strategies to mitigate the risk of negative social media reviews and build a positive brand identity. While the marketing function should own the task of monitoring, analyzing and responding to social media commentary, close collaboration with IT is imperative, for several reasons. Specifically, IT service desk processes related to managing and resolving incidents, as well as tracking incidents to ensure issues have been resolved, can be applied to the task of monitoring social media and responding to complaints in a timely manner.


Machine learning and the shipping markets. #OOTT

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There's a lot of interest around machine learning and finding patterns in data. Machine learning has taken Gary Kasparov, once at the peak of professional chess, and turned him into an author and political opponent of Putin (not exactly bright career paths). There appears to be some pretty low hanging fruit at the moment, and Amazon web services and other providers offer low cost access to processing capabilities needed. I think the sticking point for finding useful information using any of these methods of analysis will be the depth of understanding needed in trade flows to comprehend which patterns are important and the explanations for others.