Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Accelerating Convolutional Neural Networks for Mobile Applications
Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications
Squeezing Deep Learning into Mobile and Embedded Devices
Accelerating Deep Convolutional Neural Networks Using Specialized Hardware
DeepSense: A GPU-based Deep Convolutional Neural Network Framework on Commodity Mobile Devices
Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks
Efficient Mobile Implementation of A CNN-based Object Recognition System
Structured Probabilistic Pruning for Convolutional Neural Network Acceleration
A Resource-Limited Hardware Accelerator for Convolutional Neural Networks in Embedded Vision Applications
Sparse Convolutional Neural Networks
Low Cost Convolutional Neural Network Accelerator Based on Bi-Directional Filtering and Bit-Width Reduction
MobileNetV2: Inverted Residuals and Linear Bottlenecks
DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks
Striving for Simplicity: The All Convolutional Net
SPARCNet: A Hardware Accelerator for Efficient Deployment of Sparse Convolutional Networks
Efficient and accurate approximations of nonlinear convolutional networks
Understanding Convolutional Neural Networks
Quaternion Convolutional Neural Networks
Speeding up Convolutional Neural Network Training with Dynamic Precision Scaling and Flexible Multiplier-Accumulator
FlexFlow: A Flexible Dataflow Accelerator Architecture for Convolutional Neural Networks
Fast and efficient implementation of Convolutional Neural Networks on FPGA
CHARACTER RECOGNITION IN NATURAL IMAGES
Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network
chimeric antigen receptor - modified t cells in chronic lymphoid leukemia .
Automatic Readability Classification of Crowd-Sourced Data based on Linguistic and Information-Theoretic Features
Telecom strategies for service discovery in microservice environments