Deep Image: Scaling up Image Recognition

01/13/2015
by   Ren Wu, et al.
0

We present a state-of-the-art image recognition system, Deep Image, developed using end-to-end deep learning. The key components are a custom-built supercomputer dedicated to deep learning, a highly optimized parallel algorithm using new strategies for data partitioning and communication, larger deep neural network models, novel data augmentation approaches, and usage of multi-scale high-resolution images. Our method achieves excellent results on multiple challenging computer vision benchmarks.

READ FULL TEXT
research
08/07/2018

Data augmentation using synthetic data for time series classification with deep residual networks

Data augmentation in deep neural networks is the process of generating a...
research
09/13/2021

The State of the Art when using GPUs in Devising Image Generation Methods Using Deep Learning

Deep learning is a technique for machine learning using multi-layer neur...
research
09/01/2018

Evaluation of Neural Networks for Image Recognition Applications: Designing a 0-1 MILP Model of a CNN to create adversarials

Image Recognition is a central task in computer vision with applications...
research
06/28/2021

Deep Learning Image Recognition for Non-images

Powerful deep learning algorithms open an opportunity for solving non-im...
research
11/05/2020

End-to-end Deep Learning Methods for Automated Damage Detection in Extreme Events at Various Scales

Robust Mask R-CNN (Mask Regional Convolu-tional Neural Network) methods ...
research
02/05/2018

Dream Formulations and Deep Neural Networks: Humanistic Themes in the Iconology of the Machine-Learned Image

This paper addresses the interpretability of deep learning-enabled image...
research
11/02/2022

DynamicISP: Dynamically Controlled Image Signal Processor for Image Recognition

Image signal processor (ISP) plays an important role not only for human ...

Please sign up or login with your details

Forgot password? Click here to reset