首页期刊导航|Robotics & Machine Learning Daily News
期刊信息/Journal information
Robotics & Machine Learning Daily News
NewsRx
Robotics & Machine Learning Daily News

NewsRx

Robotics & Machine Learning Daily News/Journal Robotics & Machine Learning Daily News
正式出版
收录年代

    Researchers from McMaster University Report Details of New Studies and Findings in the Area of Machine Learning (Neutralnet: Development and Testing of a Machin e Learning Solution for Pulse Shape Discrimination)

    88-89页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting originating from Hamilton, Ca nada, by NewsRx correspondents, research stated, “Accuratedescription of radiat ion fields containing neutrons continues to be a difficult task to complete. Thi sdifficulty arises because of the inherent sensitivity of neutron detectors to other types of radiation, and theability of neutrons to generate secondary part icles producing mixed field environments.”

    New Findings in Machine Learning Described from University of Ljubljana (Assessm ent of ‘Golden Delicious’ Apples Using an Electronic Nose and Machine Learning t o Determine Ripening Stages)

    89-90页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on artificial intelligence is now available. According to news reportingoriginating from Ljubljana, Slove nia, by NewsRx correspondents, research stated, “Consumers often facea lack of information regarding the quality of apples available in supermarkets.”

    Researchers at Southwest University Report New Data on Artificial Intelligence ( Enhancing Healthcare Supply Chain Management Through Artificial Intelligence-dri ven Group Decision-making With Sugeno-weber Triangular Norms In a Dual Hesitant …)

    90-91页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ar tificial Intelligence. According to news reportingout of Chongqing, People’s Re public of China, by NewsRx editors, research stated, “The healthcareindustry fa ces numerous challenges in managing its supply chain efficiently, where critical decisions mustbe made promptly to ensure the availability of essential medical resources. This research introduces a novelartificial intelligence (AI) approa ch, utilizing the ‘Sugeno-Weber (SW) t-conorms and t -norms’ (SWt-CNs& t-Ns) for decision -making in a Dual Hesitant q -Rung Orthopair Fuzzy (DHq-ROF) context.”

    Findings on Robotics Reported by Investigators at Beihang University (Grasping W ith Occlusion-aware Ally Method In Complex Scenes)

    91-92页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ro botics. According to news reporting fromBeijing, People’s Republic of China, by NewsRx journalists, research stated, “Robotic arm target graspingby vision sup port is a commonly used method in grasping tasks and is usually used for multi-t argetcomplex scenes. Where vision support is generally used to identify the tar gets and to get their positions,categories and sizes.”

    Findings on Computational Intelligence Detailed by Investigators at University o f Electronic Science and Technology of China (Cviformer: Cross-view Interactive Transformer for Efficient Stereoscopic Image Super-resolution)

    92-93页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning - Compu tational Intelligence are presented in a newreport. According to news reporting from Chengdu, People’s Republic of China, by NewsRx journalists,research state d, “Inspired by the great success of the Transformer in computer vision, some wo rkshave started to explore the use of the Transformer for super-resolution (SR) . However, with regard tostereoscopic SR, which aims to recover details from in put pairs, how to efficiently integrate cross-viewinteractions into the Transfo rmer architecture is still an ongoing development.”

    Study Data from University of Vaasa Update Understanding of Artificial Intellige nce (Integrating Futures Imaginaries, Expectations and Anticipatory Practices: P ractitioners of Artificial Intelligence Between Now and Future)

    93-94页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Artificial In telligence have been published. According tonews reporting from Vaasa, Finland, by NewsRx journalists, research stated, “Artificial intelligence (AI) isa worl d-changing technology due to its abilities to learn independently, process big d ata, and automatehuman work. Imagining the socio-technical future is necessary, but challenging, in the era of AI that rapidlydeveloping technology has made t urbulent.”

    Studies from Hainan University Yield New Information about Support Vector Machin es (Feature Selection By Universum Embedding)

    94-95页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Su pport Vector Machines. According to newsreporting originating from Haikou, Peop le’s Republic of China, by NewsRx correspondents, research stated,“Feature sele ction in classification is an important task in machine learning. Inspired by th e success ofUniversum support vector machine proposed by Weston et al. on impro ving the classification ability ofclassical support vector machine, this paper considers a special type of Universum and further lets it playits role in both useful feature identification and separating hyperplane construction, aiming to improveboth the feature selection ability and classification performance of Uni versum support vector machine.”

    New Robotics Study Findings Recently Were Reported by Researchers at Nanjing Uni versity of Information Science and Technology (NUIST) (Approximation-based Admit tance Control of Robotenvironment Interaction With Guaranteed Performance)

    95-96页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Robotics have been published. According to news reportingoriginating in Nanjing, People’s Re public of China, by NewsRx journalists, research stated, “Humans areable to com pliantly interact with the environment by adapting its motion trajectory and con tact force.Robots with the human versatility can perform contact tasks more eff iciently with high motion precision.”

    Findings in the Area of Robotics Reported from Chinese Academy of Sciences (Hybr id Vision/force Cascaded Model Predictive Control of Robotic Manipulators for Au tomatic Docking Tasks)

    96-97页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Robotics have been pr esented. According to news reporting fromChangchun, People’s Republic of China, by NewsRx journalists, research stated, “This article presents ahybrid vision/ force cascaded model predictive control method for robotic manipulators utilized in automaticdocking tasks. This control method consists of force predictive co ntrol (FPC) cascaded with visualpredictive control (VPC).”

    New Robotics and Automation Data Have Been Reported by Investigators at Technica l University Munich (TU Munich) (Keep It Upright: Model Predictive Control for N onprehensile Object Transportation With Obstacle Avoidance On a Mobile Manipulat or)

    97-97页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Robotics - Robotics and Automation. Accordingto news reporting originating in M unich, Germany, by NewsRx journalists, research stated, “We considera nonprehen sile manipulation task in which a mobilemanipulator must balance objects on its end effectorwithout grasping them-known as the waiter’s problem-and move to a d esired location while avoiding staticand dynamic obstacles. In contrast to exis ting approaches, our focus is on fast online planning in responseto new and cha nging environments.”