2,282 research outputs found
ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering
We propose a novel attention based deep learning architecture for visual
question answering task (VQA). Given an image and an image related natural
language question, VQA generates the natural language answer for the question.
Generating the correct answers requires the model's attention to focus on the
regions corresponding to the question, because different questions inquire
about the attributes of different image regions. We introduce an attention
based configurable convolutional neural network (ABC-CNN) to learn such
question-guided attention. ABC-CNN determines an attention map for an
image-question pair by convolving the image feature map with configurable
convolutional kernels derived from the question's semantics. We evaluate the
ABC-CNN architecture on three benchmark VQA datasets: Toronto COCO-QA, DAQUAR,
and VQA dataset. ABC-CNN model achieves significant improvements over
state-of-the-art methods on these datasets. The question-guided attention
generated by ABC-CNN is also shown to reflect the regions that are highly
relevant to the questions
Design of a Six-Swing-Arm Wheel-Legged Chassis for Forestry and Simulation Analysis of its Obstacle-Crossing Performance
Obstacle-crossing performance is an important criterion for evaluating the power chassis of
forestry machinery. In this paper, a new six-swing-arm wheel-legged chassis (SWC&F) is
designed according to the characteristics of forest terrain, using herringbone legs to control
the ride comfort and stability of the chassis in the process of crossing obstacles. First, the kinematic
model of the SWC&F is established, the coordinate analytical expression of each wheel
centre position is derived, and the swing angle range of each wheel leg of the chassis is calculated
according to the installation position of the hydraulic cylinder. Next, the control model
of the system is constructed, and the obstacle-crossing performance of the SWC&F is analyzed
by ADAMS/Simulink co-simulation using the PID control method and conventional control
method, respectively. The results show that the maximum obstacle crossing height of the
SWC&F can reach 411.1 mm, and the chassis with PID control system has good dynamic
response characteristics and smooth motion, which meets the requirements of forest chassis
obstacle crossing design. The study can provide the foundation for the practical laws of the
physical prototype of the forest vehicle chassis
On the Uniqueness of Balanced Complex Orthogonal Design
Complex orthogonal designs (CODs) play a crucial role in the construction of
space-time block codes. Their real analog, real orthogonal designs (or
equivalently, sum of squares composition formula) have a long history. Adams et
al. (2011) introduced the concept of balanced complex orthogonal designs
(BCODs) to address practical considerations. BCODs have a constant code rate of
and a minimum decoding delay of , where is the number of
columns. Understanding the structure of BCODs helps design space-time block
codes, and it is also fascinating in its own right.
We prove, when the number of columns is fixed, all (indecomposable) balanced
complex orthogonal designs (BCODs) have the same parameters , and moreover, they are all equivalent
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