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A multiobjective prediction model with incremental learning ability by developing a multi-source filter neural network for the electrolytic aluminium process.

• Authors : Yao, Lizhong; Ding, Wei; He, Tiantian

Subjects: MACHINE learning; LEARNING ability; PROBABILITY density function

• Source: Applied Intelligence; Dec2022, Vol. 52 Issue 15, p17387-17409, 23p

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APT: The master-copy-free training method for quantised neural network on edge devices.

• Authors : Huang, Tian¹ (AUTHOR) ; Luo, Tao¹ (AUTHOR) ; Zhou, Joey Tianyi¹ (AUTHOR)

Subjects: *LEARNING ability; *POWER resources; *EDGES (Geometry)

• Source: Journal of Parallel & Distributed Computing. Aug2022, Vol. 166, p95-103. 9p.

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LFC-UNet: learned lossless medical image fast compression with U-Net.

• Authors : Hengrui Liao; Yue Li

Subjects: DIAGNOSTIC imaging; IMAGE compression; CROSS-entropy method

• Source: PeerJ Computer Science; Feb2024, p1-17, 17p

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An intelligent sliding mode controller of robotic manipulators with output constraints and high‐level adaptation.

Subjects: *MANIPULATORS (Machinery); *LEARNING ability; *ROBOTICS

• Source: International Journal of Robust & Nonlinear Control. Aug2022, Vol. 32 Issue 12, p6888-6912. 25p.

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Efficient Inverse Fractional Neural Network-Based Simultaneous Schemes for Nonlinear Engineering Applications.

• Authors : Shams, Mudassir; Carpentieri, Bruno

Subjects: MACHINE learning; NONLINEAR equations; ENGINEERING

• Source: Fractal & Fractional; Dec2023, Vol. 7 Issue 12, p849, 39p

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A Fast, Low-Cost and Simple Method for Predicting Atomic/Inter-Atomic Properties by Combining a Low Dimensional Deep Learning Model with a Fragment Based Graph Convolutional Network.

• Authors : Gao, Peng; Liu, Zonghang; Zhang, Jie

Subjects: DEEP learning; CONVOLUTIONAL neural networks; NUCLEAR magnetic resonance

• Source: Crystals (2073-4352); Dec2022, Vol. 12 Issue 12, p1740, 11p

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增强型注意力网络点击通过率预估方法.

• Authors : 陈乔松; 胡高浩; 曹宏剑

Subjects: INTERACTIVE learning; TENSOR products; LEARNING ability

• Source: Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition); Feb2023, Vol. 35 Issue 1, p147-155, 9p

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Tweaking AI software to function like a human brain improves computer's learning ability

• Source: NewsRx Health & Science. January 31, 2021, p626

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