no code implementations • 5 Nov 2022 • Haichao Zhang, Jiashi Li, Xin Xia, Kuangrong Hao, Xuefeng Xiao
Our improved backbone network can reduce the computational effort while improving the accuracy of the object detection network.
no code implementations • 26 Jul 2022 • Yudi Zhao, Kuangrong Hao, Chaochen Gu, Bing Wei
To address the trade-off problem of quality-diversity for the generated images in imbalanced classification tasks, we research on over-sampling based methods at the feature level instead of the data level and focus on searching the latent feature space for optimal distributions.
no code implementations • 20 Mar 2022 • Haichao Zhang, Kuangrong Hao, Witold Pedrycz, Lei Gao, Xuesong Tang, Bing Wei
The high-performance backbone network searched by VTCAS introduces the desirable features of convolutional neural networks into the Transformer architecture while maintaining the benefits of the multi-head attention mechanism.
no code implementations • 8 Sep 2021 • Bing Wei, Yudi Zhao, Kuangrong Hao, Lei Gao
Visual sensation and perception refers to the process of sensing, organizing, identifying, and interpreting visual information in environmental awareness and understanding.
no code implementations • 23 Mar 2021 • Haichao Zhang, Kuangrong Hao, Lei Gao, Xuesong Tang, Bing Wei
At the stage of block-level search, a relaxation method based on the gradient is proposed, using an enhanced gradient to design high-performance and low-complexity blocks.
no code implementations • 31 Jan 2021 • Bing Wei, Kuangrong Hao, Lei Gao
For the sake of recognizing and classifying textile defects, deep learning-based methods have been proposed and achieved remarkable success in single-label textile images.
no code implementations • 10 Jan 2021 • Yan Xiao, Yaochu Jin, Kuangrong Hao
First, based on the prototypical networks, we propose an adaptive mixture mechanism to add label words to the representation of the class prototype, which, to the best of our knowledge, is the first attempt to integrate the label information into features of the support samples of each class so as to get more interactive class prototypes.
no code implementations • 21 Dec 2020 • Haichao Zhang, Kuangrong Hao, Lei Gao, Bing Wei, Xuesong Tang
Deep neural networks (DNNs) have achieved remarkable success in computer vision; however, training DNNs for satisfactory performance remains challenging and suffers from sensitivity to empirical selections of an optimization algorithm for training.
no code implementations • 10 Mar 2020 • Yan Xiao, Yaochu Jin, Ran Cheng, Kuangrong Hao
With an exponential explosive growth of various digital text information, it is challenging to efficiently obtain specific knowledge from massive unstructured text information.
no code implementations • 7 Mar 2020 • Haoyu Zhang, Yaochu Jin, Ran Cheng, Kuangrong Hao
Recently, evolutionary neural architecture search (ENAS) has received increasing attention due to the attractive global optimization capability of evolutionary algorithms.