A survey on deep learning based joint source-channel coding by Tianjie MU, Xiaohui CHEN, Yiyun WANG, Lupeng MA, Dong LIU, Jing ZHOU, Wenyi ZHANG

“…Classical information theory shows that separate source-channel coding is asymptotically optimal over a point-to-point channel.As modern communication systems are becoming more sensitive to delays and bandwidth,it becomes difficult to adopt the assumption that such separate designs have unlimited computing power for encoding and decoding.Compared to joint source-channel coding,separate coding has proven to be sub-optimal when the bandwidth is limited.However,conventional joint source-channel coding schemes require complicated design.In contrast,data-driven deep learning brings new designing ideas into the paradigm.A summary of relevant research results was provided,which will help to clarify the way in which deep learning methods solve the joint source-channel coding problem and to provide an overviewof new research directions.Source compression schemes and end-to-end communication system models were firstly introduced,both based on deep learning,then two kinds of joint coding designs under different types of source,and potential problems of joint source-channel coding based on deep learning and possible future research directions were introduced.…”
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JSCC-Aided INR for High-Frequency Detail Preservation in LiDAR by Akihiro Kuwabara, Sorachi Kato, Toshiaki Koike-Akino, Takuya Fujihashi

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Finding knowledge: how youth identify their candidacy and sources of information regarding sexual and reproductive health in rural KwaZulu-Natal. South Africa by Ntombizonke A. Gumede, Siphesihle Hlongwane, Vuyiswa Nxumalo, Dumile Gumede, Maryam Shahmanesh, Janet Seeley, Guy Harling

“…Participants expected different types of information from healthcare providers, family members and peers, and had a nuanced understanding of the strengths and weaknesses of each source. Stigma related to youths’ SRH and their precarious socioeconomic circumstances limited channels for communication and the ability for shared interpersonal knowledge to impact health behavior. …”
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Trace Copilot: Automatically Locating Cryptographic Operations in Side-Channel Traces by Firmware Binary Instrumenting by Shipei Qu, Yuxuan Wang, Jintong Yu, Chi Zhang, Dawu Gu

“…For real-world attacks, the source code is typically unavailable, which poses a challenge for locating the COs thus reducing the effectiveness of many methods. …”
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Experimental Demostration of a MIMO-OFDM Underwater Optical Communication System for Reducing Alignment Angle Requirements by Boxun Li, Min Fu, Mengnan Sun, Xuefeng Liu, Bing Zheng

“…Although the underwater optical communication system (UWOC) plays an important role in many marine applications, the acquisition, pointing and tracking (APT) problems are still great challenges in a long or turbid water channel. …”
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A Scale-Aware and Discriminative Feature Learning Network for Fine-Grained Rigid Object Recognition by Yangte Gao, Chenwei Deng, Liang Chen, Zicong Zhu

“…The experimental results show that introducing only a small number of parameters during training, SD-Net, improves the performance of the models based on the ResNet and ViT by about 4.6 points. The code and dataset will be open source in the future.…”
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LEVEL APPLICATION OF GROWERS TO SMART FARMING TECHNIQUES TO CONFRONT CLIMATE CHANGE by Rayan Kadem

“…Subsequently, the data were coded and prepared for statistical analysis using SPSS software. …”
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SwinD-Net: a lightweight segmentation network for laparoscopic liver segmentation by Shuiming Ouyang, Baochun He, Huoling Luo, Fucang Jia

“…Our model effectively reduces parameter count and computational complexity, improving the inference speed while maintaining comparable accuracy. The source code will be available at https://github.com/ouyangshuiming/SwinDNet.…”
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