Results 71 to 80 of about 79,498 (272)
Scalable Task Planning via Large Language Models and Structured World Representations
Advanced Robotics Research, EarlyView.This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari +4 more
wiley +1 more source
Progressive multi-level distillation learning for pruning network
Complex & Intelligent Systems, 2023 Although the classification method based on the deep neural network has achieved excellent results in classification tasks, it is difficult to apply to real-time scenarios because of high memory footprints and prohibitive inference times.
Ruiqing Wang +9 more
doaj +1 more source
A Filter Pruning Method of CNN Models Based on Feature Maps Clustering
Applied Sciences, 2022 The convolutional neural network (CNN) has been widely used in the field of self-driving cars. To satisfy the increasing demand, the deeper and wider neural network has become a general trend.
Zhihong Wu +5 more
doaj +1 more source
Online Filter Clustering and Pruning for Efficient Convnets
, 2019 Pruning filters is an effective method for accelerating deep neural networks (DNNs), but most existing approaches prune filters on a pre-trained network directly which limits in acceleration.
Hong, Richang +3 more
core +1 more source
Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Cluster-Based Structural Redundancy Identification for Neural Network Compression
Entropy, 2022 The increasingly large structure of neural networks makes it difficult to deploy on edge devices with limited computing resources. Network pruning has become one of the most successful model compression methods in recent years.
Tingting Wu +3 more
doaj +1 more source
Forecasting with artificial network models [PDF]
, 2002 This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The statistical approach to artificial neural networks modelling developed by the author is compared to linear modelling and to other three ...
Rech, Gianluigi
core
Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks
, 2019 Architecture optimization, which is a technique for finding an efficient neural network that meets certain requirements, generally reduces to a set of multiple-choice selection problems among alternative sub-structures or parameters.
Choe, Yoonsuck +3 more
core +1 more source
Advanced Science, EarlyView.Chronic periodontitis elevates circulating CRP, which enters the hippocampus to upregulate BMP4 in oligodendrocyte precursor cells (OPCs), thereby impairing neurogenesis and inducing anxiety/depression‐like behaviors in rats. Counteracting this pathway, CRP deficiency helps confer functional resilience to OPCs.
Lingjie Li +9 more
wiley +1 more source
Vojnotehnički Glasnik, 2015 This paper presents the training, testing and pruning of a feedforward neural network with one hidden layer that was used for the prediction of the vowel ”a”.
Danijela D. Protić
doaj +1 more source