text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
large an different However, is there number practical of models in now use. astonishingly | However, there is now an astonishingly large number of different models in practical use. | 38,600 |
The semantic trackers. of Siamese as distractors, are the considered robustness which backgrounds hinders always | The semantic backgrounds are always considered as distractors, which hinders the robustness of Siamese trackers. | 38,601 |
long-term we tracking. learning this focus and Siamese networks accurate In distractor-aware for paper, on | In this paper, we focus on learning distractor-aware Siamese networks for accurate and long-term tracking. | 38,602 |
in at are end, traditional Siamese trackers this features used first. analyzed To | To this end, features used in traditional Siamese trackers are analyzed at first. | 38,603 |
the learned features makes imbalanced data observe the less distribution that of training discriminative. We | We observe that the imbalanced distribution of training data makes the learned features less discriminative. | 38,604 |
asset digital in are management power for development system. grid need Chinese of enterprises | Chinese power grid enterprises are in need for development of digital asset management system. | 38,605 |
the have training the a priori all in known However, operations to be phase. | However, all the operations have to be known a priori in the training phase. | 38,606 |
transit consumers rail large Electric systems are energy. of | Electric rail transit systems are large consumers of energy. | 38,607 |
substations. reversible and technologies storage systems optimization, (onboard include: and timetable energy These train wayside), | These technologies include: train timetable optimization, energy storage systems (onboard and wayside), and reversible substations. | 38,608 |
generation. approach uses planning It to a story | It uses a planning approach to story generation. | 38,609 |
pre- the the raw sensor need process data. eliminates or The post network to | The network eliminates the need to pre- or post process the raw sensor data. | 38,610 |
great supervised unsupervised challenges. and methods face Existing | Existing supervised and unsupervised methods face great challenges. | 38,611 |
this novel data be Cross-domain in utilized framework. synthetic fully could | Cross-domain synthetic data could be fully utilized in this novel framework. | 38,612 |
ensure well are transferred perception capability domains. strategies across to depth proposed Different different learned | Different strategies are proposed to ensure learned depth perception capability well transferred across different domains. | 38,613 |
dataset. show results depth state-of-the-art of on KITTI extensive experiments Our monocular estimation | Our extensive experiments show state-of-the-art results of monocular depth estimation on KITTI dataset. | 38,614 |
architecture. connectivity U-Net a We the pattern design for new | We design a new connectivity pattern for the U-Net architecture. | 38,615 |
the connections flow across efficiently information could U-Nets. coupling The more make | The coupling connections could make the information flow more efficiently across U-Nets. | 38,616 |
parameter feature makes across reuse U-Net each very U-Nets The efficient. | The feature reuse across U-Nets makes each U-Net very parameter efficient. | 38,617 |
estimation. evaluate U-Nets of datasets pose the coupled human on benchmark We two | We evaluate the coupled U-Nets on two benchmark datasets of human pose estimation. | 38,618 |
are number accuracy parameter and model compared. the Both | Both the accuracy and model parameter number are compared. | 38,619 |
accuracy CU-Net comparable obtains The state-of-the-art as methods. | The CU-Net obtains comparable accuracy as state-of-the-art methods. | 38,620 |
the retrospective most not existing datasets consist of sequences. FLAIR do However, of | However, most of the existing retrospective datasets do not consist of FLAIR sequences. | 38,621 |
process methods the and process imputation, of modality the segmentation. of imputation Existing missing separate | Existing missing modality imputation methods separate the process of imputation, and the process of segmentation. | 38,622 |
are segmentation. Iso-depth via regions determined superpixel | Iso-depth regions are determined via superpixel segmentation. | 38,623 |
model. a dissertation, probabilistic two index solutions provide we In this to fit | In this dissertation, we provide two solutions to fit a probabilistic index model. | 38,624 |
entire unique into of set partitions. data consists splitting the The first algorithm | The first algorithm consists of splitting the entire data set into unique partitions. | 38,625 |
fit the aggregate model these, then On each of and we the estimates. | On each of these, we fit the model and then aggregate the estimates. | 38,626 |
we in the work, this address variation. weather of that is One challenges, particular | One of the particular challenges, that we address in this work, is weather variation. | 38,627 |
low-level can not model properly. do produce that drastic Seasonal changes, features classic changes appearance | Seasonal changes can produce drastic appearance changes, that classic low-level features do not model properly. | 38,628 |
Our contributions paper in are twofold. this | Our contributions in this paper are twofold. | 38,629 |
the outperform the best Our art of field. the of results state | Our best results outperform the state of the art of the field. | 38,630 |
procedure, time-consuming and error-prone. This is however, | This procedure, however, is time-consuming and error-prone. | 38,631 |
Using mitosis ensembling combined detector. stain invariant with a network it during in resulted training | Using it during training combined with network ensembling resulted in a stain invariant mitosis detector. | 38,632 |
issues two metric important are Feature person for and learning re-identification. representation | Feature representation and metric learning are two important issues for person re-identification. | 38,633 |
applications technology medium can find in link power reconfigurable ac-dc distribution. interesting Parallel voltage | Parallel ac-dc reconfigurable link technology can find interesting applications in medium voltage power distribution. | 38,634 |
suitable time makes applications. it for The of fast model real-time execution the | The fast execution time of the model makes it suitable for real-time applications. | 38,635 |
overcome. nanoscale Powering with challenge major such wireless communications is supply, however, a energy to | Powering such wireless communications with nanoscale energy supply, however, is a major challenge to overcome. | 38,636 |
text-to-image heterogeneous synthesis in homogeneous lie main of and two The gaps: issues the gaps. | The main issues of text-to-image synthesis lie in two gaps: the heterogeneous and homogeneous gaps. | 38,637 |
discriminative exploit these of we (e.g. problems, generic addressing models excellent capability the For | For addressing these problems, we exploit the excellent capability of generic discriminative models (e.g. | 38,638 |
datasets two Experiments conducted our are the to verify SDN. proposed of widely-used on effectiveness | Experiments on two widely-used datasets are conducted to verify the effectiveness of our proposed SDN. | 38,639 |
This them applications. makes for preferable real-world | This makes them preferable for real-world applications. | 38,640 |
training require datasets. large networks such However, very | However, such networks require very large training datasets. | 38,641 |
laborious. difficult is data training Engineering the and/or | Engineering the training data is difficult and/or laborious. | 38,642 |
As on results the obtain consequence, KITTI we benchmarks. a state-of-the-art | As a consequence, we obtain state-of-the-art results on the KITTI benchmarks. | 38,643 |
code manuscript. this The matlab available is in | The matlab code is available in this manuscript. | 38,644 |
any bias. in and terms we As for logic approximation, efficiency subjective computational evaluate of | As for any approximation, we evaluate subjective logic in terms of computational efficiency and bias. | 38,645 |
IHC to co-registered H&E slides the were The slides. | The H&E slides were co-registered to the IHC slides. | 38,646 |
imagery airplane a Automatic in detection variety of applications. aerial has | Automatic airplane detection in aerial imagery has a variety of applications. | 38,647 |
rotation-and-scale a solve invariant generator. present challenges, these we proposal airplane To | To solve these challenges, we present a rotation-and-scale invariant airplane proposal generator. | 38,648 |
non-maximum suppression remove to detections. Finally, employ we duplicate | Finally, we employ non-maximum suppression to remove duplicate detections. | 38,649 |
annotations as Moreover, an of airplanes box-level using estimate direction the we achievement. the extra | Moreover, we estimate the direction of the airplanes using box-level annotations as an extra achievement. | 38,650 |
We images. dermoscopic lesion strategy for superpixel-based on present skin segmenting a | We present a superpixel-based strategy for segmenting skin lesion on dermoscopic images. | 38,651 |
as mean superpixel RGB The used color merging criterion. of was each | The mean RGB color of each superpixel was used as merging criterion. | 38,652 |
the a framework realize is the challenge. in multi-view fusion How such primary to joint | How to realize the multi-view fusion in such a joint framework is the primary challenge. | 38,653 |
clustering DMJC-T KL are objective. a Both under optimized and DMJC-S like divergence | Both DMJC-S and DMJC-T are optimized under a KL divergence like clustering objective. | 38,654 |
learn network in an rectification We the network and end-to-end recognition manner. | We learn the rectification network and recognition network in an end-to-end manner. | 38,655 |
graph. Our model consists one four tensorflow final aggregated models single into of | Our final model consists of four single models aggregated into one tensorflow graph. | 38,656 |
a problem. two-stage this tacking We deep for framework learning present | We present a two-stage deep learning framework for tacking this problem. | 38,657 |
new such and image Our portrait extrapolation. removal portrait editing applications method enables as occlusion | Our method enables new portrait image editing applications such as occlusion removal and portrait extrapolation. | 38,658 |
several performance datasets. state-of-the-art on in results a This | This results in a state-of-the-art performance on several datasets. | 38,659 |
The knowledge representation ASP presents a extends language paper with aggregates. $\mathcal{A}log$ which | The paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates. | 38,660 |
capture high imaging frame to ultrasound Cardiac rapid motion. requires order a in rate | Cardiac ultrasound imaging requires a high frame rate in order to capture rapid motion. | 38,661 |
expense acquisition introducing block This shortens artifacts. the of at time the | This shortens the acquisition time at the expense of introducing block artifacts. | 38,662 |
improve quality. MLA we the propose In data-driven image this learning-based to a paper, approach | In this paper, we propose a data-driven learning-based approach to improve the MLA image quality. | 38,663 |
endoscopy capsule diagnosis Wireless (WCE) gastrointestinal mean for effective an disorders. of is | Wireless capsule endoscopy (WCE) is an effective mean for diagnosis of gastrointestinal disorders. | 38,664 |
of the simplified Both MLP and computational CNN number reduce are operations. to structures | Both CNN and MLP structures are simplified to reduce the number of computational operations. | 38,665 |
convolutional regularization spatial for strategies neural (e.g. with networks) | convolutional neural networks) with strategies for spatial regularization (e.g. | 38,666 |
models conditional as such fields). graphical random | graphical models such as conditional random fields). | 38,667 |
dominate the to started re-identification Deep video-based progress have methods person learning (re-id). research of | Deep learning methods have started to dominate the research progress of video-based person re-identification (re-id). | 38,668 |
lack and real-world scalability video surveillance Therefore, they in severely practicality applications. | Therefore, they severely lack scalability and practicality in real-world video surveillance applications. | 38,669 |
employed can scheme. our readily standard CNNs DAL Existing be within | Existing standard CNNs can be readily employed within our DAL scheme. | 38,670 |
promising in Convolutional Recently, Neural have (SR). super-resolution performance (CNNs) Networks shown | Recently, Convolutional Neural Networks (CNNs) have shown promising performance in super-resolution (SR). | 38,671 |
branch. IRL, as master pre-trained first typical select we a In SR network a | In IRL, first we select a typical SR pre-trained network as a master branch. | 38,672 |
comprehensive, for a for Finally, implications cost-effective malaria discuss strategy we the control. | Finally, we discuss the implications for a comprehensive, cost-effective strategy for malaria control. | 38,673 |
It component software critical based has and systems. is vision applications spread for wide a | It has wide spread applications and is a critical component for vision based software systems. | 38,674 |
plane causes in and the printed phenomenon, misregistration, image. halo gap color artifacts This called | This phenomenon, called color plane misregistration, causes gap and halo artifacts in the printed image. | 38,675 |
algorithms embedded are for Our or designed firmware implementation. software | Our algorithms are designed for software or embedded firmware implementation. | 38,676 |
based the are first of use The algorithms two look-up tables on (LUTs). | The first two algorithms are based on the use of look-up tables (LUTs). | 38,677 |
in firmware particularly printers. low-cost the attractive of for algorithm embedded This is formatter-based implementation | This algorithm is particularly attractive for implementation in the embedded firmware of low-cost formatter-based printers. | 38,678 |
business. is dataset applied model open real the to an for And | And the model is applied to an open dataset for real business. | 38,679 |
without with any labelled data. supervised been facial attributes, having | facial attributes, without having been supervised with any labelled data. | 38,680 |
index data of pseudo-Rsquared proposed. to new is goodness-of-fit VBGF A the models LFD for | A new pseudo-Rsquared index for the goodness-of-fit of VBGF models to LFD data is proposed. | 38,681 |
curve and robust, bootstrap-based are for presented New, fitting methods discussed. | New, robust, bootstrap-based methods for curve fitting are presented and discussed. | 38,682 |
regularized proposed interval-valued for neural (RANN) artificial is prediction. network A data | A regularized artificial neural network (RANN) is proposed for interval-valued data prediction. | 38,683 |
in to introduce reduce paper, method we arising MLT. this In artifacts a data-driven the | In this paper, we introduce a data-driven method to reduce the artifacts arising in MLT. | 38,684 |
lane-level accuracy for autonomous localization is very vehicles. important The | The lane-level localization accuracy is very important for autonomous vehicles. | 38,685 |
Satellite The e.g. Global (GNSS), System Navigation | The Global Navigation Satellite System (GNSS), e.g. | 38,686 |
classification with was compared the method. The SVM performance CNN the of based method | The performance of the SVM based classification method was compared with the CNN method. | 38,687 |
from SFP scratch prune enables capacity the and Large model train to simultaneously. | Large capacity enables SFP to train from scratch and prune the model simultaneously. | 38,688 |
pruning outperforms filter scratch SFP Empirically, the previous methods. from | Empirically, SFP from scratch outperforms the previous filter pruning methods. | 38,689 |
effective CNN many Moreover, advanced for approach demonstrated has architectures. been our | Moreover, our approach has been demonstrated effective for many advanced CNN architectures. | 38,690 |
separates This from avoids recovering high frequencies, denoising over-smoothing. which features low-frequency | This separates recovering low-frequency features from denoising high frequencies, which avoids over-smoothing. | 38,691 |
signed (inside/outside) The distances the samples. output balances to the curve | The output curve balances the signed distances (inside/outside) to the samples. | 38,692 |
connectivity. on parameter-free is Our fast determined the algorithm local the neighborhoods operates by and | Our algorithm is parameter-free and operates fast on the local neighborhoods determined by the connectivity. | 38,693 |
solver system by handle to bounds. We augment a least-squares linear a also constrained | We augment a least-squares solver constrained by a linear system to also handle bounds. | 38,694 |
samplers MCMC Carlo computation. an (SMC) attractive Sequential Bayesian for form alternative Monte to | Sequential Monte Carlo (SMC) samplers form an attractive alternative to MCMC for Bayesian computation. | 38,695 |
on rejuvenate used their kernels strongly depends Markov particles. performance to However, the | However, their performance depends strongly on the Markov kernels used to rejuvenate particles. | 38,696 |
Learning problem data important vision. transformation an is visual representations of computer in invariant | Learning transformation invariant representations of visual data is an important problem in computer vision. | 38,697 |
classification for results demonstrated Deep networks have and image tasks. convolutional video remarkable | Deep convolutional networks have demonstrated remarkable results for image and video classification tasks. | 38,698 |
computation Neural achieve superior performance wider bring Deeper (CNNs) and expensive Convolutional but Networks cost. | Deeper and wider Convolutional Neural Networks (CNNs) achieve superior performance but bring expensive computation cost. | 38,699 |
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