Results 51 to 60 of about 343,225 (391)
Effect of Mechanical Pruning on Olive Yield in a High-Density Olive Orchard: An Account of 14 Years
Agronomy, 2022 In Portugal, the study of mechanical pruning in olive orchards began in 1997. Trials were carried out in traditional orchards, and the obtained results revealed that mechanical pruning can contribute to the reduction in pruning costs without a reduction ...
António Dias +3 more
doaj +1 more source
Importance Estimation for Neural Network Pruning [PDF]
Computer Vision and Pattern Recognition, 2019 Structural pruning of neural network parameters reduces computational, energy, and memory transfer costs during inference. We propose a novel method that estimates the contribution of a neuron (filter) to the final loss and iteratively removes those with
Pavlo Molchanov +4 more
semanticscholar +1 more source
Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning [PDF]
Workshop on Representation Learning for NLP, 2020 Pre-trained universal feature extractors, such as BERT for natural language processing and VGG for computer vision, have become effective methods for improving deep learning models without requiring more labeled data.
Mitchell A. Gordon +2 more
semanticscholar +1 more source
Dynamic Structure Pruning for Compressing CNNs [PDF]
arXiv, 2023 Structure pruning is an effective method to compress and accelerate neural networks. While filter and channel pruning are preferable to other structure pruning methods in terms of realistic acceleration and hardware compatibility, pruning methods with a finer granularity, such as intra-channel pruning, are expected to be capable of yielding more ...
arxiv
PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017 This paper presents a method for adding multiple tasks to a single deep neural network while avoiding catastrophic forgetting. Inspired by network pruning techniques, we exploit redundancies in large deep networks to free up parameters that can then be ...
Arun Mallya, Svetlana Lazebnik
semanticscholar +1 more source
, 2009 Large and complex meta-models such as those of Uml and its profiles are growing due to modelling and inter-operability needs of numerous stakeholders. The complexity of such meta-models has led to coining of the term meta-muddle. Individual users often exercise only a small view of a meta-muddle for tasks ranging from model creation to construction of ...
Sen, Sagar +3 more
openaire +5 more sources
Blind Adversarial Pruning: Balance Accuracy, Efficiency and Robustness [PDF]
, 2020 With the growth of interest in the attack and defense of deep neural networks, researchers are focusing more on the robustness of applying them to devices with limited memory. Thus, unlike adversarial training, which only considers the balance between accuracy and robustness, we come to a more meaningful and critical issue, i.e., the balance among ...
arxiv +1 more source
Genomic Analysis of Drosophila Neuronal Remodeling: A Role for the RNA-Binding Protein Boule as a Negative Regulator of Axon Pruning [PDF]
, 2008 Drosophila mushroom body (MB) {gamma} neurons undergo axon pruning during metamorphosis through a process of localized degeneration of specific axon branches.
Hoopfer, Eric D. +3 more
core +1 more source
Alternate-year walnut pruning can boost yields, cut cost
California Agriculture, 1994 Annual pruning was compared to nonpruning for 8 years and to two alternate-year pruning treatments for 4 years in a mature, full-canopied ‘Ashley’ walnut orchard.
W Olson, D Ramos, R Snyder
doaj +3 more sources
Revista Brasileira de Fruticultura, 2017 The objective of this study was to evaluate the effect of pruning intensity on yield and quality of blueberries fruits. It was evaluated the cultivar Misty. The treatments were: absence of pruning; light pruning; regular pruning and drastic pruning.
GISELY CORREA DE MOURA +3 more
doaj +1 more source