DEEP learningThe editorial discusses the importance of resource-efficient deep learning for computer vision applications, particularly in mobile settings where resource constraints are a concern. The special issue focuses on training and inference of budget-aware models to maximize available data and ...
{Content-Adaptive Downsampling in Convolutional Neural Networks}, author = {Hesse, Robin and Schaub-Meyer, Simone and Roth, Stefan}, booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), The 6$^\text{th}$ Efficient Deep Learning for Computer Vision (...
Computer Vision has a long history of academic research, and recent advances in deep learning have provided significant improvements in the ability to understand visual content. As a result of these research advances on problems such as object classification, object detection, and image segmentation, ...
Using pretrained model We include pretrained model of KITTI2015 and KITTI2012 inpretrain. To use pretrained model of KITTI2015(similar for KITTI2012), run:th inference_match_subimg.lua -g 0 --model split_win37_dep9 --data_version kitti2015 --data_root pretrain/kitti2015/sample_img --mod...
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition (NeurIPS 2022) arXivcodeOpenReview 在计算机视觉任务中,Full fine-tuning 通常直接去fine tune整个预训练模型,这会带来较大的计算资源的需求。 受NLP中相关工作的启发(如Parameter-Efficient Transfer Learning for NLP),作者探索了在CV任务中...
With the increasing popularity of herbal medicine, high standards of the high quality control of herbs becomes a necessity, with the herb recognition as one of the great challenges. Due to the complicated processing procedure of the herbs, methods of man
* 其他: Published in Efficient Deep Learning for Computer Vision (ECV) CVPR Workshop 2022* 摘要: 近年来,已经提出了新颖的激活功能来提高神经网络的性能,并且与Relu对应物相比,它们的性能卓越。但是,在某些环境中,复杂激活的可用性受到限制,并且通常只支持relu。在本文中,我们提出的方法可用于通过在模型训练...
2021-TPDS-The Deep Learning Compiler: A Comprehensive Survey 2021-JMLR-Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks 2021.6-Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better 2022-IJCAI-Recent Advances ...
如果点击有误:https://github.com/LeBron-Jian/DeepLearningNote 摘要 我们针对移动端以及嵌入式视觉的应用提出了一类有效的模型叫MobileNets。MobileNets 是基于一种流线型结构使用深度可分离卷积来构造权重深度神经网络。我们介绍两个能够有效权衡延迟和准确率的简单的全局超参数。这些超参数允许模型构造器能够根据特定问题...
Minerva - A Scalable and Highly Efficient Training Platform for Deep Learning。 本文是关于Minerva简介的一篇译文。本人刚接触深度学习方向,专业术语了解甚少,斗胆翻译了这篇文章,有诸多语言不通顺和不准确之处。望与同