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Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

Advanced Intelligent Discovery, EarlyView.
This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando, Naoto Watanabe, Chihiro Sekine, Shogen Sekiguchi, Ohmi Fuchiwaki   +4 more
wiley   +1 more source

PlantCTCIP: Chromatin Interaction Prediction Using Convolutional Neural Network and Transformer in Plants. [PDF]

Plant Biotechnol J
Wang Z, Zhou S, Guo Z, Ning Z, Cai J, Zhao R, Xie A, Li Q, Zhang J, Zhao Y, Li P, Si H, Yan J, Peng Y, Liu J.   +14 more
europepmc   +1 more source

Convolutional neural network models describe the encoding subspace of local circuits in auditory cortex. [PDF]

Nat Neurosci
Wingert JC, Parida S, Norman-Haignere SV, David SV.   +3 more
europepmc   +1 more source

Risk identification model for power enterprises based on convolutional neural network. [PDF]

Sci Rep
Pan W, Liu F.
europepmc   +1 more source

Hypothalamic atrophy in progressive supranuclear palsy, assessed by convolutional neural network-based automatic segmentation. [PDF]

J Neurol
Kassubek J, Höglinger GU, Zůza A, Kreiser K, Roselli F, DESCRIBE-PSP Study Group, Müller HP.   +6 more
europepmc   +1 more source

Percutaneous nephrostomy guidance by a convolutional-neural-network-based optical coherence tomography endoscope. [PDF]

Commun Eng
Wang C, Calle P, Yan F, Zhang Q, Fung KM, Yu Z, Duguay SG, Vanlandingham WB, Bradley NA, Patel SG, Nave B, Hostetler C, Milam A, Pan C, Tang Q.   +14 more
europepmc   +1 more source

ResSeMo: deep convolutional neural network integration for high-accuracy waste classification and efficient processing. [PDF]

Sci Rep
Liu T, Li B, Wang Z.
europepmc   +1 more source

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IFCNN: A general image fusion framework based on convolutional neural network

Information Fusion, 2020
In this paper, we propose a general image fusion framework based on the convolutional neural network, named as IFCNN. Inspired by the transform-domain image fusion algorithms, we firstly utilize two convolutional layers to extract the salient image ...
Yu Zhang, Yu Liu
exaly   +2 more sources