Source: novuslight.com Euresys announced the availability of a new Deep Learning library: EasySegment works in unsupervised mode. After being trained with “good” images only, it can detect and segment anomalies and defects in new images. EasySegment works with any image resolution, supports data augmentation and masks, and is compatible with CPU and GPU processing. The new Read More
Tag: deep learning
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Source: In recent years, cutting-edge computational technologies are increasingly being applied in clinical settings in order to provide higher quality of healthcare. Furthermore, huge amount of biomedical data is continuously acquired and stored from ever accurate medical devices. Conversely, in the scientific research community, there is a growing necessity to develop more optimized methodologies that Read More
Source: news-medical.net Several technologies have been developed over the past few years that are pushing the boundaries of our scientific knowledge to new heights. As these technologies develop scientists are looking into ways of using them in tandem, to produce more accurate results and new ways of approaching the problems of the modern scientific industry. Read More
Source: nasdaq.com It’s no secret that Apple (NASDAQ: AAPL) has spent a great deal of time, money, and resources to make its devices — particularly the iPhone — smarter using artificial intelligence (AI). One of the factors that differentiates Apple from the other companies developing the technology is its consistent commitment to data privacy. To advance that agenda, Read More
Source: /i-hls.com Currently, almost every company integrates Artificial Intelligence into its products, including deep learning. “The availability of current computing power, alongside labeled databases and trained networks that can be easily adapted for solving new problems – these are the factors that helped the deep learning field to finally grow”, said Roy Fahn, who leads the Read More
Source: photonics.com AUSTIN, Texas, and SAN DIEGO, Jan. 14, 2020 — Using deep learning techniques, researchers from the Salk Institute have developed a new microscopy approach that could make microscopic techniques used for brain imaging 16 times faster. The researchers trained their deep learning system using data from the Texas Advanced Computing Center (TACC) at The University Read More
Source: drugtargetreview.com Researchers have designed a novel approach to use deep learning to improve their understanding of how proteins interact in the body. According to the team, their findings could result in more accurate structure models of protein interactions in various diseases and better drug designs that target protein interactions. The study, conducted at Purdue Read More
Source: sdtimes.com Amazon has launched a new open-source library that will make it easier for developers to deploy machine learning models. With AutoGluon, Amazon aims to help developers deploy their models using just a few lines of code. “We developed AutoGluon to truly democratize machine learning, and make the power of deep learning available to all developers,” Read More
Source: infoworld.com Amazon has created an open source toolkit for automated machine learning, called AutoGluon, designed to make it easier for software developers to take advantage of deep learning models in their applications. AutoGluon is intended for both machine learning experts and beginners, the company says. Officially launched January 9, AutoGluon lets developers harness machine learning models with image, Read More
Source: devclass.com AWS has quietly open sourced an open source tool kit it claims will “democratise” machine learning by removing much of the hand tooling data scientists currently fill their time with. The cloud to everything giant’s AutoGluon slipped onto GitHub last year, under the Apache 2 license, but AWS is only now cranking up the publicity Read More
Source: healthcarepackaging.com Despite the advance of automation technologies into virtually every realm of manufacturing, quality inspection remains a task commonly reserved for humans. One of the primary reasons for this is that factors such as random product placement, atypical defects, and variations in lighting can be problematic for traditional machine vision systems. This difficulty is Read More
Source: towardsdatascience.com Machine learning is a powerful concept of finding patterns from data. However, if you have tried building a machine model from scratch, you should be aware of the challenges involved in designing a scalable machine learning workflow. Labeling, training, and fine-tuning parameters are all time-consuming activities involved in building a machine learning model Read More
Source: telecompaper.com Singapore operator M1 and Singapore Institute of Technology (SIT) have signed a research collaboration agreement, to jointly research and develop artificial intelligence (AI) deep learning algorithms and methodology to upgrade the planning, operations and maintenance of large and complex mobile networks. M1 and SIT plan to jointly develop AI services to reduce manual Read More
Source: geospatialworld.net Artificial Intelligence (AI) has the peculiar ability to simultaneously amaze, enthrall and intimidate. The possibilities of AI are innumerable and beyond the scope of our imagination. AI would be the bedrock of the era of connected mobility, automation and Industry 4.0, powering everything from analytics, decision-making, agriculture, logistics, to construction, aerospace and robotics. Read More
Source: hrtechnologist.com “Deep-learning will transform every single industry,” said Andrew Ng, a Chinese-American scientist excelling in machine learning and AI. McKinsey’s forecast on machine learning backs up his statement claiming that by 2030, AI will have a significant impact of $13 trillion on the global economy. The Human Resource department will also witness the influence Read More
Source: expresscomputer.in The human brain is complicated and for all the right reasons. A pathway of neurons, millions of cells, creating a response to stimuli and observation, all of this working simultaneously to help our brain give an appropriate response. Furthering its greatness, the brain is constantly observing and learning. A well-known learning method- ‘learning by Read More
Source: phys.org During the past years, artificial intelligence (AI)—the capability of a machine to mimic human behavior—has become a key player in high-tech areas like drug development projects. AI tools help scientists to uncover the secret behind the big biological data using optimized computational algorithms. AI methods such as deep neural network improves decision making Read More
Source: mashable.com Artificial intelligence and deep learning might bring to mind pictures of Will Smith’s misadventures in I, Robot, but in reality, these are the technologies behind tomorrow’s world. In fact, by 2030, PwC predicts nearly 40 percent of all U.S. jobs could be replaced by AI and automation. That’s a bit frightening, but if you’re one of Read More
Source: techxplore.com Recent advances in machine learning have enabled the development of techniques to detect and recognize human emotions. Some of these techniques work by analyzing electroencephalography (EEG) signals, which are essentially recordings of the electrical activity of the brain collected from a person’s scalp. Most EEG-based emotion classification methods introduced over the past decade Read More
Source: therobotreport.com StradVision Inc. last week said it had raised $27 million in Series B funding. The Seoul, South Korea-based company makes vision processing technology for autonomous vehicles and advanced driver assistance systems, or ADAS. Posco Capital led the round, which included investment from IDG Capital, Industrial Bank of Korea, Lighthouse Combined Investment, LSS Private Equity, Read More
Source: information-age.com A recent study by Peltarion has revealed that just 1% of decision makers have extensively deployed deep learning, despite high hopes 99% of participants in ‘The Peltarion AI Decision Makers Survey: Are enterprises ready to go deep with AI?’ expressed belief that deep learning would transform their industry, and 98% said that their company were Read More
Source: deccanchronicle.com Hyderabad: As scientific disciplines go, the field of ‘Deep Learning’ is but an infant. However, it will soon have a disruptive effect on the field of drug design, experts say. They were speaking at a panel discussion as part of the ongoing international conference on high performance computing in Hyderabad on Wednesday. Deep learning, Read More
Source: techxplore.com Taking good-quality photographs can be a challenging task, as it typically requires finding ideal locations, angles and lighting conditions. Although artistic pictures have so far primarily been taken by human photographers, in recent years, some researchers have started investigating the possibility of taking pictures automatically using robots. To this end, a team of Read More
Source: idgconnect.com Deep learning is overtaking more classic machine learning methods according to a recent study of AI industry leaders across Europe, which included Amazon, Google and JP Morgan. The report, entitled Deep Learning: Opportunities and Best Practice, published by CognitionX and Peltarion, highlighted several factors that are enabling wider uptake, such as increased data Read More
Source: arstechnica.com In particular, the more potential inputs you have to an algorithm, the more out of control your scaling problem gets when analyzing its problem space. This is where MACH, a research project authored by Rice University’s Tharun Medini and Anshumali Shrivastava, comes in. MACH is an acronym for Merged Average Classifiers via Hashing, Read More
Source: technologynetworks.com Deep learning, a type of artificial intelligence, can boost the power of MRI in predicting attention deficit hyperactivity disorder (ADHD), according to a study published in Radiology: Artificial Intelligence. Researchers said the approach could also have applications for other neurological conditions. The human brain is a complex set of networks. Advances in functional Read More
Source: techxplore.com Carnegie Mellon University computer scientists have taken a deep learning method that has revolutionized face recognition and other image-based applications in recent years and redirected its power to explore the relationship between genes. The trick, they say, is to transform massive amounts of gene expression data into something more image-like. Convolutional neural networks Read More
Source: forbes.com This year, we have seen all the hype around AI Deep Learning. With recent innovations, deep learning demonstrated its usefulness in performing tasks such as image recognition, voice recognition, price forecasting, across many industries. It’s easy to overestimate deep learning’s capabilities and pretend it’s the magic bullet that will allow AI to obtain General Intelligence. In truth, we are Read More
Source: investors-corner.bnpparibas-am.com Deep learning and asset pricing models Following our first post, we now discuss the “Deep Learning in Asset Pricing” paper of Guanhao Feng from City University of Hong Kong. This proposes a departure from machine learning research that attempts to forecast directly financial asset returns and stumbles on the problem of a low signal-to-noise ratio in such returns. Instead, and to Read More
Source: techxplore.com Most deep-learning algorithms perform well when trained on large sets of labeled data, but their performance tends to decline when processing new data. Researchers worldwide have thus been trying to develop techniques that could improve the ability of these algorithms to generalize well across both new and previously processed data, enabling what is Read More