Results 161 to 170 of about 183,434 (340)

Reed-Solomon Hybrid Codes for Optical Communications

Journal of Engineering and Sustainable Development, 2013
The astonishing performance of concatenated codes attracted many researchers and this has resulted in an explosive amount of literature since their introduction few years ago.
Awatif Ali Jafaar
doaj  

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Compressive hyperspectral image classification using a 3D coded convolutional neural network

, 2021
Hao Zhang, Xu Ma, Xianhong Zhao, Gonzalo R. Arce   +3 more
openalex   +1 more source

Quantum Teleportation Error Suppression Algorithm Based on Convolutional Neural Networks and Quantum Topological Semion Codes [PDF]

, 2022
Qian Cao, Haowen Wang, Yingjie Qu, Yun-Jia Xue, Shumei Wang   +4 more
openalex   +1 more source

A convolutional code-based sequence analysis model and its application. [PDF]

Int J Mol Sci, 2013
Liu X, Geng X.
europepmc   +1 more source

Cellpose+, a Morphological Analysis Tool for Feature Extraction of Stained Cell Images

Advanced Intelligent Discovery, EarlyView.
We introduce Cellpose plus, a morphological and geometrical analysis tool for feature extraction of stained cell images built over Cellpose, a state‐of‐the‐art cell segmentation framework. We also introduce a dataset of DAPI and FITC stained cells to which our new method is applied.
Israel A. Huaman, Fares D. E. Ghorabe, Sofya S. Chumakova, Alexandra A. Pisarenko, Alexey E. Dudaev, Tatiana G. Volova, Galina A. Ryltseva, Sviatlana A. Ulasevich, Ekaterina I. Shishatskaya, Ekaterina V. Skorb, Pavel S. Zun   +10 more
wiley   +1 more source

Design and Evaluation of Adaptive (Serial/Parallel) Concatenated Convolutional Codes

Journal of Engineering and Sustainable Development, 2006
In this paper, parallel Concatenated Convolutional Codes (PCCCs) is modeled as a special case of Serial Concatenated Convolutional Code (SCCCs). Consequently, resulting in Adaptive (parallel/serial) concatenated convolutional code in which the same ...
Khamis A. Zidan, Raghad Z. Yousif
doaj  

An Efficient QP Variable Convolutional Neural Network Based In-loop Filter for Intra Coding [PDF]

, 2020
Zhijie Huang, Xiaopeng Guo, Mingyu Shang, Jie Gao, Jun Sun   +4 more
openalex   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Polarization-adjusted Convolutional (PAC) Codes: Fano Decoding vs List Decoding.

, 2020
Mohammad Rowshan, Andreas Burg, Emanuele Viterbo   +2 more
openalex   +1 more source