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Neural Architecture Search

160 papers with code ยท Methodology
Subtask of AutoML

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Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation

31 Mar 2020

To satisfy the stringent requirements on computational resources in the field of real-time semantic segmentation, most approaches focus on the hand-crafted design of light-weight segmentation networks.

NEURAL ARCHITECTURE SEARCH REAL-TIME SEMANTIC SEGMENTATION

Disturbance-immune Weight Sharing for Neural Architecture Search

29 Mar 2020

To alleviate the performance disturbance issue, we propose a new disturbance-immune update strategy for model updating.

NEURAL ARCHITECTURE SEARCH

NPENAS: Neural Predictor Guided Evolution for Neural Architecture Search

28 Mar 2020

Neural architecture search (NAS) is a promising method for automatically finding excellent architectures. Commonly used search strategies such as evolutionary algorithm, Bayesian optimization, and Predictor method employs a predictor to rank sampled architectures.

NEURAL ARCHITECTURE SEARCH

CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Network

28 Mar 2020

3D Convolution Neural Networks (CNNs) have been widely applied to 3D scene understanding, such as video analysis and volumetric image recognition.

3D MEDICAL IMAGING SEGMENTATION NEURAL ARCHITECTURE SEARCH SCENE UNDERSTANDING TEMPORAL ACTION LOCALIZATION

DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search

27 Mar 2020

One common way is searching on a smaller proxy dataset (e. g., CIFAR-10) and then transferring to the target task (e. g., ImageNet).

NEURAL ARCHITECTURE SEARCH

Are Labels Necessary for Neural Architecture Search?

26 Mar 2020

Existing neural network architectures in computer vision --- whether designed by humans or by machines --- were typically found using both images and their associated labels.

NEURAL ARCHITECTURE SEARCH

DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation

26 Mar 2020

Neural Architecture Search (NAS) has shown great potentials in automatically designing scalable network architectures for dense image predictions.

NEURAL ARCHITECTURE SEARCH SEMANTIC SEGMENTATION

GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet

25 Mar 2020

The training efficiency is thus boosted since the training space has been greedily shrunk from all paths to those potentially-good ones.

IMAGE CLASSIFICATION NEURAL ARCHITECTURE SEARCH

ASFD: Automatic and Scalable Face Detector

25 Mar 2020

In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design.

NEURAL ARCHITECTURE SEARCH

BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models

24 Mar 2020

Without extra retraining or post-processing steps, we are able to train a single set of shared weights on ImageNet and use these weights to obtain child models whose sizes range from 200 to 1000 MFLOPs.

NEURAL ARCHITECTURE SEARCH