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 are pre sented in a new report. According to newsreporting originating in Harbin, Peopl e’s Republic of China, by NewsRx journalists, research stated, “Theshear bearin g capacity of confined concrete columns subjected to lateral cyclic loading is a n importantmechanical property in investigating seismic behavior of concrete bu ildings. However, it is still difficult toaccurately predict shear bearing capa city of confined concrete columns using traditional analysis methodsowing to it s complex mechanical principle and indeterminate multivariable interrelationship .”
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 originating fromSeoul, South Korea, by NewsRx editors , the research stated, “Most studies of consumer preferences andexpectations fo r home robots focus on either older adults or single-person households (SPHs).”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in robotic systems. According to news reporting originatingfrom Changzhou, People’s Repub lic of China, by NewsRx correspondents, research stated, “The precisebagging of immature peaches by the fruit bagging robot requires the identification of the target youngfruits as well as the acquisition of their growth angles. The netwo rk models employed in single detectionalgorithms exhibit complexity and pose ch allenges for deployment on mobile terminals as they heavily relyon the availabi lity of labeled samples.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on artificial intelligen ce have been presented. According to newsoriginating from Fes, Morocco, by News Rx editors, the research stated, “Stereo camera self-calibration isa complex ch allenge in computer vision applications such as robotics, object tracking, surve illance and3D reconstruction.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning. According to news reporting fromGolden, Colorado, by NewsRx journali sts, research stated, “- This paper proposes a scalable architecturefor predict ing antenna performance using various data- informed machine learning (DIML) met hods. By utilizing the computation power of graphics processing units (GPUs), th e architecture takes advantage ofhardware (HW) acceleration from the beginning of electromagnetic (EM) full-wave simulation to the finalmachine learning (ML) validation.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Researchers detail new data in Machine Learning. According to news reporting originating in Harbin,People’s Republic of China, b y NewsRx journalists, research stated, “This work tackles an integrated orderba tching, picker assignment, batch sequencing, and picker routing problem in wareh ouse environments.A Learning-Aided Iterated Local Search (LILS) is proposed to efficiently find its high-quality solutions.”
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 artificial intelligence. According to news reportingout of Warangal, India, by NewsRx editors, research stated, “ABSTRACT: Spur dikes are pivotal elementsin r iver training, serving to mitigate the dynamic alterations induced by river degr adation and aggradation.”
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 reportingfrom Louisville, Kentucky, by NewsRx journalists, research stated, “This study presents an innovative deeple arning framework for kidney segmentation in magnetic resonance imaging (MRI) dat a.”Our news correspondents obtained a quote from the research from University of Lo uisville: “Theframework integrates both kidney appearance and prior shape infor mation using a residual cycle-consistentgenerative adversarial network (CycleGA N). An appearance-based shape prior model is developed, utilizingiso-circular c ontours generated from the kidney centroid and employing the fast marching level sets methodfor shape extraction. By utilizing the kidney centroid and matching cross-circular iso-circular contours’appearance, the proposed appearance-based shape prior model remains invariant to translation, rotation,and scaling, elim inating the need for alignment. Additionally, a novel weighted loss function, th e H-Loss,is introduced to enhance segmentation performance and prevent overfitt ing. The proposed approach istested on 34 blood-oxygen-level-dependent (BOLD) g rafts from patients in our kidney transplant program,achieving an average dice score of 92%.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on artificial intell igence are discussed in a new report. According tonews originating from Hassan 1st University by NewsRx correspondents, research stated, “Amid growingglobal u ncertainty and increasingly complex disruptions, the ability of supply chains to rapidly adapt andrecover is critical.”
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 out of Chengdu, People’s Repu blic of China, by NewsRx editors, research stated, “The chemicalreactions betwe en certain interstellar molecules are exothermic in nature and barrierless in th e entrancechannel, allowing these reactions to occur rapidly even at low astron omical temperatures, e.g., C andO2 interaction. Obtaining detailed rovibrationa l transition parameters for the reaction between C andO2, such as state-selecte d rate coefficients, is crucial for studying the associated atmospheric and astronomical environments.”
NETL
NSTL