Výsledky vyhledávání - Adaptive residual conventional neural networks with encoder-decoder

Light Weight Encoder-Decoder for Underwater Images in Internet of Underwater Things (IoUT) Autor Nair, Rashmi S, Agrawal, Rohit, Domnic, S

“… Conventional compression techniques used for terrestrial environment, causes ringing artefacts due to the variable characteristics of underwater…”
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An intelligent framework of VVC-based video compression and bit rate reduction using vision transformer-based adaptive residual attention densenet Autor Padmapriya, D., Ameelia Roseline, A.

“… Since the conventional models are normally complex and the parameter’s amount is highly large, it is needed to develop a lightweight model for VVC…”
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Structure-preserving low-dose computed tomography image denoising using a deep residual adaptive global context attention network Autor Zhang, Yuanke, Hao, Dejing, Lin, Yingying, Sun, Wanxin, Zhang, Jinke, Meng, Jing, Ma, Fei, Guo, Yanfei, Lu, Hongbing, Li, Guangshun, Liu, Jianlei

“… Deep convolutional neural networks (CNNs) have shown their potential in improving LDCT image quality…”
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DCANet: A Dual-Branch Cross-Scale Feature Aggregation Network for Remote Sensing Image Semantic Segmentation Autor Yang, Yanhong, Wang, Fei, Zhang, Haozheng, Xue, Yushan, Zhang, Guodao, Chen, Shengyong

“… features, thus limiting model performance. In this article, we introduce DCANet, a dual-branch cross-scale feature aggregation network based on an encoder-decoder framework, incorporating visual-state-space (VSS…”
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JPEG steganalysis with combined dense connected CNNs and SCA-GFR Autor Yang, Jianhua, Kang, Xiangui, Wong, Edward K., Shi, Yun-Qing

“… In this paper, we propose a 32-layer convolutional neural network (CNN) involving feature reuse by concatenating all features from previous layers…”
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