查看更多>>摘要：News editors obtained the following quote from the background information suppli ed by the inventors: “ “Field of the Invention “The present invention is in the field of machine learning and more particularly to the generation of datasets for training of machine learning systems. “Related Art “Videos are increasingly becoming the most preferred media for marketers. Produc ts with videos are known to provide higher conversions since it adds a lot of tr ust and value to the product being sold. Unfortunately, creating videos can be a difficult tasks that can require a great deal of skill and specific software to ols. “In the fashion domain, each fashion season include lots of new products. With f ast fashion, seasons can change every week. Product development in fashion can i nvolve a lot of nuance in the design. A shirt may be structurally the same as an other shirt, but it can vary in color print, neckline, sleeve, fit etc. These va riations are created by the designer. Hence, it is important for the video gener ation platform to also identify these nuances and uniqueness of the product and showcase the same.”
查看更多>>摘要：The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “Fruits such as strawberries and grapes, and gre en and yellow vegetables such as asparagus and tomatoes, are delicate and prone to damage as well as have high unit prices, compared with grain such as rice and wheat. Such delicate crops with high unit prices are harvested manually one by one to prevent damage caused to the crops at the time of harvest. Therefore, har vesting, e.g., fruits and green and yellow vegetables, places a large physical b urden on a producer, as compared with, e.g., grain that can be harvested efficie ntly on a large scale by using harvesting machines such as combine harvesters. T he physically demanding harvesting operation involves difficulty in securing lab or force, and therefore tends to place an increased burden on a producer. Thus, crop harvesting systems using a multi-joint robot arm are known.
查看更多>>摘要：inventors: “Field “The disclosed embodiments generally relate to techniques for using machine-lear ning (ML) models to perform prognostic-surveillance operations based on time-ser ies sensor signals. More specifically, the disclosed embodiments relate to a tec hnique for characterizing the susceptibility of an ML model to follow signal deg radation and evaluating possible mitigation strategies. “Related Art “Large numbers of sensors are presently deployed to monitor the operational heal th of critical assets in a large variety of business-critical systems. For examp le, a medium-sized computer data center can include over 1,000,000 sensors monit oring thousands of servers, a modern passenger jet can include 75,000 sensors, a n oil refinery can include over 1,000,000 sensors, and even an ordinary car can have over 100 sensors. These sensors produce large volumes of time-series sensor data, which can be used to perform prognostic-surveillance operations to facili tate detecting incipient anomalies. This makes it possible to take remedial acti on before the incipient anomalies develop into failures in the critical assets.
查看更多>>摘要：The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “Autonomous and semi-autonomous industrial robot ic equipment is increasingly being used in outside work environments such as on construction sites, building sites, mining sites, and industrial sites. In many cases the equipment comprises robots which can grasp, manipulate and place objec ts. One such system is a robotic construction robot in which a telescoping artic ulated arm is mounted on a truck, and a conveyor transports bricks to a layhead mounted at the end of the arm which includes a lay robot, which lays the bricks. When the brick arrives at the layhead, adhesive is applied to it and a gripper assembly of the lay robot grips it and moves it to a lay location where the bric k is placed, preferably to within sub-mm accuracy. The applicant’s brick laying construction robot is described in more detail in co-pending applications PCT/AU 2017/050731, PCT/AU2017/050730, PCT/AU2017/050728, PCT/AU2017/050739, PCT/AU2017 /050738 and PCT/AU2018/050698.
查看更多>>摘要：From the background information supplied by the inventors, news correspondents o btained the following quote: “Voice/chatbots are conversational applications tha t often plug into other applications and services (e.g., virtual personal assist ants, schedulers, reminders, ordering systems, retail websites etc.). These voic e/chatbots provide to the user a communication interface to these other applicat ions and services that attempts to provide an interaction that mimics the experi ence of interacting with a real person. Giving the recent rapid growth in the nu mber of applications and services utilizing voice/chatbots and the diversity dom ains in which voice/chatbots are being deployed (e.g., health services, retail s ector, entertainment services, etc.), there is an ever-increasing need for tools that build voice/chatbot conversations in an efficient and effective manner.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from os f.io: “Explainable Artificial Intelligence (XAI) seeks to render Artificial Intelligen ce (AI) models transparent and comprehensible, potentially increasing trust and confidence in AI recommendations. “This research explores the realm of XAI within unsupervised educational machine learning, a relatively under-explored topic within Learning Analytics (LA). It introduces an XAI framework designed to elucidate clustering-based personalized recommendations for educators.
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