Results 21 to 30 of about 4,888,790 (252)
Canadian Journal of Remote Sensing, 2021 High-resolution images exhibit wide field of vision, high background complexity, special angle of view, rotation, and small objects, thus making automatic object detection a challenging problem. Recently, this problem has been studied by many researchers
Lianyu Cao, Xiaolu Zhang, Zhaoshun Wang
doaj +1 more source
FastDARTSDet: Fast Differentiable Architecture Joint Search on Backbone and FPN for Object Detection
Applied Sciences, 2022 Neural architecture search (NAS) is a popular branch of automatic machine learning (AutoML), which aims to search for efficient network structures.
Chunxian Wang +7 more
doaj +1 more source
Group Differentiable Architecture Search
IEEE Access, 2021 Differentiable architecture search (DARTS) has received great attention due to its simplicity and efficiency. However, there are two annoying problems. One is that searched architecture of normal cell tends to be shallow.
Chaoyuan Shen, Jinhua Xu
doaj +1 more source
MS-DARTS: Mean-Shift Based Differentiable Architecture Search
CoRR, 2021 14pages
Jun-Wei Hsieh +5 more
openaire +2 more sources
DARTS: Differentiable Architecture Search
CoRR, 2018 This paper addresses the scalability challenge of architecture search by formulating the task in a differentiable manner. Unlike conventional approaches of applying evolution or reinforcement learning over a discrete and non-differentiable search space, our method is based on the continuous relaxation of the architecture representation, allowing ...
Hanxiao Liu +2 more
openaire +4 more sources
D-DARTS: Distributed Differentiable Architecture Search
, 2021 Differentiable ARchiTecture Search (DARTS) is one of the most trending Neural Architecture Search (NAS) methods, drastically reducing search cost by resorting to Stochastic Gradient Descent (SGD) and weight-sharing.
Tabia, Hedi +3 more
core +2 more sources
DARTS+: Improved Differentiable Architecture Search with Early Stopping
CoRR, 2019 Recently, there has been a growing interest in automating the process of neural architecture design, and the Differentiable Architecture Search (DARTS) method makes the process available within a few GPU days. However, the performance of DARTS is often observed to collapse when the number of search epochs becomes large.
Hanwen Liang +6 more
openaire +2 more sources
DARTS-ASR: Differentiable Architecture Search for Multilingual Speech Recognition and Adaptation [PDF]
Interspeech 2020, 2020 Accepted at INTERSPEECH ...
Yi-Chen Chen +3 more
openaire +2 more sources
RC-DARTS: Resource Constrained Differentiable Architecture Search
CoRR, 2019 Recent advances show that Neural Architectural Search (NAS) method is able to find state-of-the-art image classification deep architectures. In this paper, we consider the one-shot NAS problem for resource constrained applications. This problem is of great interest because it is critical to choose different architectures according to task complexity ...
Xiaojie Jin +6 more
openaire +2 more sources
IET Computer Vision, 2022 Although YOLOv4 has a high detection accuracy, its backbone network CSPDarknet53 requires a large number of parameters, which reduces the inference speed of the detection network to some extent.
Zhiqiang Xing, Xi Chen, Fengqian Pang
doaj +1 more source