20,053 research outputs found
Collaborative Spatio-temporal Feature Learning for Video Action Recognition
Spatio-temporal feature learning is of central importance for action
recognition in videos. Existing deep neural network models either learn spatial
and temporal features independently (C2D) or jointly with unconstrained
parameters (C3D). In this paper, we propose a novel neural operation which
encodes spatio-temporal features collaboratively by imposing a weight-sharing
constraint on the learnable parameters. In particular, we perform 2D
convolution along three orthogonal views of volumetric video data,which learns
spatial appearance and temporal motion cues respectively. By sharing the
convolution kernels of different views, spatial and temporal features are
collaboratively learned and thus benefit from each other. The complementary
features are subsequently fused by a weighted summation whose coefficients are
learned end-to-end. Our approach achieves state-of-the-art performance on
large-scale benchmarks and won the 1st place in the Moments in Time Challenge
2018. Moreover, based on the learned coefficients of different views, we are
able to quantify the contributions of spatial and temporal features. This
analysis sheds light on interpretability of the model and may also guide the
future design of algorithm for video recognition.Comment: CVPR 201
A Layer Decomposition-Recomposition Framework for Neuron Pruning towards Accurate Lightweight Networks
Neuron pruning is an efficient method to compress the network into a slimmer
one for reducing the computational cost and storage overhead. Most of
state-of-the-art results are obtained in a layer-by-layer optimization mode. It
discards the unimportant input neurons and uses the survived ones to
reconstruct the output neurons approaching to the original ones in a
layer-by-layer manner. However, an unnoticed problem arises that the
information loss is accumulated as layer increases since the survived neurons
still do not encode the entire information as before. A better alternative is
to propagate the entire useful information to reconstruct the pruned layer
instead of directly discarding the less important neurons. To this end, we
propose a novel Layer Decomposition-Recomposition Framework (LDRF) for neuron
pruning, by which each layer's output information is recovered in an embedding
space and then propagated to reconstruct the following pruned layers with
useful information preserved. We mainly conduct our experiments on ILSVRC-12
benchmark with VGG-16 and ResNet-50. What should be emphasized is that our
results before end-to-end fine-tuning are significantly superior owing to the
information-preserving property of our proposed framework.With end-to-end
fine-tuning, we achieve state-of-the-art results of 5.13x and 3x speed-up with
only 0.5% and 0.65% top-5 accuracy drop respectively, which outperform the
existing neuron pruning methods.Comment: accepted by AAAI19 as ora
User-differentiated hierarchical key management for the bring-your-own-device environments
To ensure confidentiality, the sensitive electronic data held within a corporation is always carefully encrypted and stored in a manner so that it is inaccessible to those parties who are not involved. During this process, the specific manners of how to keep, distribute, use, and update keys which are used to encrypt the sensitive data become an important thing to be considered. Through use of hierarchical key management, a technique that provides access controls in multi-user systems where a portion of sensitive resources shall only be made available to authorized users or security ordinances, required information is distributed on a need-to-know basis. As a result of this hierarchical key management, time-bound hierarchical key management further adds time controls to the information access process. There is no existing hierarchical key management scheme or time-bound hierarchical key management scheme which is able to differentiate users with the same authority. When changes are required for any user, all other users who have the same access authorities will be similarly affected, and this deficiency then further deteriorates due to a recent trend which has been called Bring-Your-Own-Device. This thesis proposes the construction of a new time-bound hierarchical key management scheme called the User-Differentiated Two-Layer Encryption-Based Scheme (UDTLEBC), one which is designed to differentiate between users. With this differentiation, whenever any changes are required for one user during the processes of key management, no additional users will be affected during these changes and these changes can be done without interactions with the users. This new scheme is both proven to be secure as a time-bound hierarchical key management scheme and efficient for use in a BYOD environment
Low-mass Active Galactic Nuclei on the Fundamental Plane of Black Hole Activity
It is widely known that in active galactic nuclei (AGNs) and black hole X-ray
binaries (BHXBs), there is a tight correlation among their radio luminosity
(), X-ray luminosity () and BH mass (\mbh), the so-called
`fundamental plane' (FP) of BH activity. Yet the supporting data are very
limited in the \mbh regime between stellar mass (i.e., BHXBs) and
10\,\msun\ (namely, the lower bound of supermassive BHs in common
AGNs). In this work, we developed a new method to measure the 1.4 GHz flux
directly from the images of the VLA FIRST survey, and apply it to the type-1
low-mass AGNs in the \cite{2012ApJ...755..167D} sample. As a result, we
obtained 19 new low-mass AGNs for FP research with both \mbh\ estimates (\mbh
\approx 10^{5.5-6.5}\,\msun), reliable X-ray measurements, and (candidate)
radio detections, tripling the number of such candidate sources in the
literature.Most (if not all) of the low-mass AGNs follow the standard
radio/X-ray correlation and the universal FP relation fitted with the combined
dataset of BHXBs and supermassive AGNs by \citet{2009ApJ...706..404G}; the
consistency in the radio/X-ray correlation slope among those accretion systems
supports the picture that the accretion and ejection (jet) processes are quite
similar in all accretion systems of different \mbh. In view of the FP relation,
we speculate that the radio loudness (i.e., the luminosity ratio
of the jet to the accretion disk) of AGNs depends not only on Eddington ratio,
but probably also on \mbh.Comment: ApJ accepte
- …