Zobrazeno 1 - 10
of 6 177
pro vyhledávání: '"Pascal programming language"'
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:2425-2439
Accurate object detection requires correct classification and high-quality localization. Currently, most of the single shot detectors (SSDs) conduct simultaneous classification and regression using a fully convolutional network. Despite high efficien
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7e9bdbe24ec1f416fbb0e16f33031ba
https://doi.org/10.1109/tnnls.2021.3106641
https://doi.org/10.1109/tnnls.2021.3106641
Publikováno v:
IEEE Transactions on Multimedia. 25:267-279
Weakly supervised object detection (WSOD aims to train object detectors by using only image-level annotations. Many recent works on WSOD adopt multiple instance detection networks (MIDN, which usually generate a certain number of proposals and regard
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e35dcf9193c1e017eed3f737f605ce5
https://doi.org/10.1109/tmm.2021.3125130
https://doi.org/10.1109/tmm.2021.3125130
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 33:213-227
Deep learning methods have achieved significant progress in the presence of correctly annotated datasets in instance segmentation. However, object classes in large-scale datasets are sometimes ambiguous, which easily causes confusion. Besides, limite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f767aa12a2b8fc2761678915e8ce5d0
https://doi.org/10.1109/tcsvt.2021.3109084
https://doi.org/10.1109/tcsvt.2021.3109084
Publikováno v:
CVPR
We study the notion of consistency between a 3D shape and a 2D observation and propose a differentiable formulation which allows computing gradients of the 3D shape given an observation from an arbitrary view. We do so by reformulating view consisten
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4c358686036a7839e82f6c2ac3de76b
https://doi.org/10.1109/tpami.2019.2898859
https://doi.org/10.1109/tpami.2019.2898859
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:6484-6493
One-shot semantic segmentation poses the challenging task of segmenting object regions from unseen categories with only one annotated example as guidance. Thus, how to effectively construct robust feature representations from the guidance image is cr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23b962ff47784c4cb623b327a8f94ca8
https://doi.org/10.1109/tnnls.2021.3081693
https://doi.org/10.1109/tnnls.2021.3081693
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 44:8082-8096
Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmentation, i.e., training accurate semantic segmentation models using bound
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32ad380dbceaed02baaae613d0764a05
https://doi.org/10.1109/tpami.2021.3083269
https://doi.org/10.1109/tpami.2021.3083269
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:4991-5003
Most of the recent image segmentation methods have tried to achieve the utmost segmentation results using large-scale pixel-level annotated data sets. However, obtaining these pixel-level annotated training data is usually tedious and expensive. In t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af6cece788831c0fe19503c5ca4a0ef3
https://doi.org/10.1109/tnnls.2021.3066850
https://doi.org/10.1109/tnnls.2021.3066850
Autor:
Luke Kljucaric, Alan D. George
Publikováno v:
HPEC
As computer architectures continue to integrate application-specific hardware, it is critical to understand the relative performance of devices for maximum app acceleration. The goal of benchmarking suites, such as MLPerf for analyzing machine-learni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::630971c7634ff465471e573149e5c237
https://doi.org/10.1145/3594221
https://doi.org/10.1145/3594221
Publikováno v:
IEEE Transactions on Cybernetics. 52:4850-4854
Over the recent years, a number of deep learning approaches are successfully introduced to tackle the problem of image in-painting for achieving better perceptual effects. However, there still exist obvious hole-edge artifacts in these deep learning-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d403df751f06de5140d4ed97ecd8888b
https://doi.org/10.1109/tcyb.2021.3105398
https://doi.org/10.1109/tcyb.2021.3105398
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 44:3082-3095
In this paper, we propose a binarized neural network learning method (BiDet) for efficient object detection. Conventional network binarization methods directly quantize the weights and activations in one-stage or two-stage detectors with constrained
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ecef146a1b2de9d503357eb6895cd90
https://doi.org/10.1109/tpami.2021.3050464
https://doi.org/10.1109/tpami.2021.3050464