2,410 research outputs found
Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal
Deep Convolutional Neural Networks (CNNs) are widely employed in modern
computer vision algorithms, where the input image is convolved iteratively by
many kernels to extract the knowledge behind it. However, with the depth of
convolutional layers getting deeper and deeper in recent years, the enormous
computational complexity makes it difficult to be deployed on embedded systems
with limited hardware resources. In this paper, we propose two
computation-performance optimization methods to reduce the redundant
convolution kernels of a CNN with performance and architecture constraints, and
apply it to a network for super resolution (SR). Using PSNR drop compared to
the original network as the performance criterion, our method can get the
optimal PSNR under a certain computation budget constraint. On the other hand,
our method is also capable of minimizing the computation required under a given
PSNR drop.Comment: This paper was accepted by 2018 The International Symposium on
Circuits and Systems (ISCAS
Cytochrome P450 Epoxygenase CYP2J2 G-50T Polymorphism is an Independent Genetic Prognostic Risk Factor and Interacts with Smoking Cessation After Index Premature Myocardial Infarction
Multi-Robot Object Transport Motion Planning with a Deformable Sheet
Using a deformable sheet to handle objects is convenient and found in many
practical applications. For object manipulation through a deformable sheet that
is held by multiple mobile robots, it is a challenging task to model the
object-sheet interactions. We present a computational model and algorithm to
capture the object position on the deformable sheet with changing robotic team
formations. A virtual variable cables model (VVCM) is proposed to simplify the
modeling of the robot-sheet-object system. With the VVCM, we further present a
motion planner for the robotic team to transport the object in a
three-dimensional (3D) cluttered environment. Simulation and experimental
results with different robot team sizes show the effectiveness and versatility
of the proposed VVCM. We also compare and demonstrate the planning results to
avoid the obstacle in 3D space with the other benchmark planner.Comment: 8 pages, 10 figures, accepted by RAL&CASE 2022 in June 24, 202
Management of Tuberculosis in Taiwan:A Look into the Shared Responsibilities of the Government, General Public and Medical Students
Tuberculosis (TB) is a deadly infectious disease worldwide due to its high incidenceand mortality rate. Its impact on Taiwan is no exception. This paper aims to examineeffectiveness of national policies on TB control, assess public awareness, and evaluatewhether involvement of medical students would have a positive effect towards TBcontrol in Taiwan.Literatures were first reviewed to assess effectiveness of Directly Observed Treatment,Short-course (DOTS). Although there is limited improvement in treatment success inTaiwan, there is an overall positive effect.Questionnaires designed to assess public knowledge and behaviors revealedinadequate public knowledge about DOTS, which could have led to the lack ofdistinct success in the national policy. Healthcare workshops were conducted by medical students, with survey resultsshowing a significant improvement in participants’ knowledge. Thus, medicalstudents are recommended to engage in healthcare activities to effectively aid TBcontrol.
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