Good practice in CNN feature transfer
The objective of this paper is the effective transfer of the Convolutional Neural Network
(CNN) feature in image search and classification. Systematically, we study three facts in …
(CNN) feature in image search and classification. Systematically, we study three facts in …
Unsupervised learning using pretrained CNN and associative memory bank
Q Liu, S Mukhopadhyay - 2018 International Joint Conference …, 2018 - ieeexplore.ieee.org
Deep Convolutional features extracted from a comprehensive labeled dataset, contain
substantial representations which could be effectively used in a new domain. Despite the …
substantial representations which could be effectively used in a new domain. Despite the …
OpenMP parallelization and optimization of graph-based machine learning algorithms
We investigate the OpenMP parallelization and optimization of two novel data classification
algorithms. The new algorithms are based on graph and PDE solution techniques and …
algorithms. The new algorithms are based on graph and PDE solution techniques and …
cvpaper. challenge in 2016: futuristic computer vision through 1,600 papers survey
arXiv:1707.06436v1 [cs.CV] 20 Jul 2017 Page 1 arXiv:1707.06436v1 [cs.CV] 20 Jul 2017
CVPAPER.CHALLENGE IN 2016, JULY 2017 1 cvpaper.challenge in 2016: Futuristic …
CVPAPER.CHALLENGE IN 2016, JULY 2017 1 cvpaper.challenge in 2016: Futuristic …
Systems and methods for content-based indexing of videos at web-scale
MR Hamid - US Patent 11,341,185, 2022 - Google Patents
Techniques for content-based indexing of videos at web-scale are described. As one
example, a computer-implemented method includes receiving a video file, splitting the video …
example, a computer-implemented method includes receiving a video file, splitting the video …
OpenMP Parallelization and Optimization of Graph-Based Machine Learning Algorithms
We investigate the OpenMP parallelization and optimization of two novel data classification
algorithms. The new algorithms are based on graph and PDE solution techniques and …
algorithms. The new algorithms are based on graph and PDE solution techniques and …
[图书][B] High Performance Computing and Real Time Software for High Dimensional Data Classification
Z Meng - 2018 - search.proquest.com
We present high performance computing and real time software for high dimensional data
classification. We investigate the OpenMP parallelization and optimization of two graph …
classification. We investigate the OpenMP parallelization and optimization of two graph …
[PDF][PDF] CNN Features Off-the-Shelf: Clustering and Finetune-free
Q Liu, S Mukhopadhyay - ltrc.lsu.edu
Deep convolutional features learned from a largescale labeled dataset, contain substantial
representations which could be effectively used in a new domain. Despite the fact that …
representations which could be effectively used in a new domain. Despite the fact that …
cvpaper. challenge in 2015-A review of CVPR2015 and DeepSurvey
H Kataoka, Y Miyashita, T Yamabe, S Shirakabe… - arXiv preprint arXiv …, 2016 - arxiv.org
The" cvpaper. challenge" is a group composed of members from AIST, Tokyo Denki
Univ.(TDU), and Univ. of Tsukuba that aims to systematically summarize papers on …
Univ.(TDU), and Univ. of Tsukuba that aims to systematically summarize papers on …
[PDF][PDF] cvpaper. challenge in CVPR2015 CVPR2015 のまとめ
片岡裕雄， 宮下侑大， 山辺智晃… - 電子情報通信学会 …, 2015 - hirokatsukataoka.net
あらまし cvpaper. challenge は産総研・東京電機大学・筑波大学のメンバーで構成される合同
グループであり, コンピュータビジョンやパターン認識分野の論文を体系的にまとめることを目的として …
グループであり, コンピュータビジョンやパターン認識分野の論文を体系的にまとめることを目的として …