no code implementations • 8 Mar 2024 • Xin Zhu, Ahmet Enis Cetin
Furthermore, with the assistance of the block MHT layer, the proposed blind normalized SVGD algorithm achieves a higher preamble detection accuracy and throughput than other state-of-the-art detection methods.
no code implementations • 8 Mar 2024 • Xin Zhu, Hongyi Pan, Yury Velichko, Adam B. Murphy, Ashley Ross, Baris Turkbey, Ahmet Enis Cetin, Ulas Bagci
Random samples drawn from latent space are then incorporated with a prototypical corrected image to generate multiple plausible images.
no code implementations • 20 Dec 2023 • Haohan Wang, Wei Feng, Yang Lu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Lixing Bo, Jingping Shao
Furthermore, for products with specific and fine-grained requirements in layout, elements, etc, a Personality-Wise Generator is devised to learn such personalized style directly from a reference image to resolve textual ambiguities, and is trained in a self-supervised manner for more efficient training data usage.
no code implementations • 14 Dec 2023 • Zhaochen Li, Fengheng Li, Wei Feng, Honghe Zhu, An Liu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Jingping Shao, Zhenglu Yang
At the planning stage, we propose a PlanNet to generate the layout of the product and other visual components considering both the appearance features of the product and semantic features of the text, which improves the diversity and rationality of the layouts.
no code implementations • 4 Oct 2023 • Xin Zhu, Daoguang Yang, Hongyi Pan, Hamid Reza Karimi, Didem Ozevin, Ahmet Enis Cetin
In comparison to the linear layer, the DCST layer reduces the number of trainable parameters and improves the accuracy of data reconstruction.
1 code implementation • 18 Sep 2023 • Hongyi Pan, Bin Wang, Zheyuan Zhang, Xin Zhu, Debesh Jha, Ahmet Enis Cetin, Concetto Spampinato, Ulas Bagci
However, it neglects background interference in the amplitude spectrum.
no code implementations • 15 Sep 2023 • Xin Zhu, Hongyi Pan, Salih Atici, Ahmet Enis Cetin
Traditional preamble detection algorithms have low accuracy in the grant-based random access scheme in massive machine-type communication (mMTC).
no code implementations • 15 Sep 2023 • Xin Zhu, Hongyi Pan, Shuaiang Rong, Ahmet Enis Cetin
The latent space data is transmitted to the receiver.
1 code implementation • 26 Jun 2023 • Yun Guo, Wei Feng, Zheng Zhang, Xiancong Ren, Yaoyu Li, Jingjing Lv, Xin Zhu, Zhangang Lin, Jingping Shao
Product image segmentation is vital in e-commerce.
1 code implementation • 15 Jun 2023 • Fengheng Li, An Liu, Wei Feng, Honghe Zhu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Jingping Shao
To advance research in this field, we have constructed a poster layout dataset named CGL-Dataset V2.
1 code implementation • 27 May 2023 • Hongyi Pan, Xin Zhu, Salih Atici, Ahmet Enis Cetin
In this paper, we propose a novel Hadamard Transform (HT)-based neural network layer for hybrid quantum-classical computing.
no code implementations • 13 Mar 2023 • Hongyi Pan, Emadeldeen Hamdan, Xin Zhu, Salih Atici, Ahmet Enis Cetin
Trainable soft-thresholding layers, that remove noise in the transform domain, bring nonlinearity to the transform domain layers.
1 code implementation • 5 Dec 2022 • Xi Zhao, Wei Feng, Zheng Zhang, Jingjing Lv, Xin Zhu, Zhangang Lin, Jinghe Hu, Jingping Shao
Recently, segmentation-based methods are quite popular in scene text detection, which mainly contain two steps: text kernel segmentation and expansion.
1 code implementation • 15 Nov 2022 • Hongyi Pan, Xin Zhu, Zhilu Ye, Pai-Yen Chen, Ahmet Enis Cetin
To improve the estimation precision, we propose a neural network that uses a novel Discrete Cosine Transform (DCT) layer to denoise and decorrelates the data.
no code implementations • 15 Nov 2022 • Hongyi Pan, Xin Zhu, Salih Atici, Ahmet Enis Cetin
In this paper, we propose a novel Discrete Cosine Transform (DCT)-based neural network layer which we call DCT-perceptron to replace the $3\times3$ Conv2D layers in the Residual neural Network (ResNet).
no code implementations • 22 Apr 2019 • Guanbin Li, Xin Zhu, Yirui Zeng, Qing Wang, Liang Lin
Specifically, by analyzing the symbiosis and mutual exclusion of AUs in various facial expressions, we organize the facial AUs in the form of structured knowledge-graph and integrate a Gated Graph Neural Network (GGNN) in a multi-scale CNN framework to propagate node information through the graph for generating enhanced AU representation.
no code implementations • ICCV 2017 • Wanli Ouyang, Kun Wang, Xin Zhu, Xiaogang Wang
In this CC-Net, there are many cascade stages.
1 code implementation • 23 Feb 2017 • Wanli Ouyang, Ku Wang, Xin Zhu, Xiaogang Wang
In this CC-Net, the cascaded classifier at a stage is aided by the classification scores in previous stages.