Convolution Smooth: A Post-Training Quantization Method for Convolutional Neural Networks by Yongyuan Chen, Zhendao Wang

Subjects: “…Convolutional neural network…”
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Post-Disaster Building Damage Segmentation Using Convolutional Neural Networks by Revaldi Rahmatmulya, Agung Teguh Wibowo Almais, Mokhamad Amin Hariyadi

“…Effective and efficient actions are needed to assist in the recovery following natural disasters, one of which is aiding in the identification of building damage levels post-disaster. To address this issue, this research proposes a system capable of performing segmentation to determine the level of building damage post-natural disaster using convolutional neural network methods. …”
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ClipQ: Clipping Optimization for the Post-Training Quantization of Convolutional Neural Network by Yiming Chen, Hui Zhang, Chen Zhang, Yi Liu

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Lost-minimum post-training parameter quantization method for convolutional neural network by Fan ZHANG, Yun HUANG, Zizhuo FANG, Wei GUO

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An ensemble convolutional neural network model for brain stroke prediction using brain computed tomography images by Most. Jannatul Ferdous, Rifat Shahriyar

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Lifetime prediction of epoxy coating using convolutional neural networks and post processing image recognition methods by Fandi Meng, Yufan Chen, Jianning Chi, Huan Wang, Fuhui Wang, Li Liu

“…Initially, a targeted image recognition approach containing convolutional neural network (CNN) and post-processing was constructed for the crack area detection. …”
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Learning EEG Representations With Weighted Convolutional Siamese Network: A Large Multi-Session Post-Stroke Rehabilitation Study by Shuailei Zhang, Kai Keng Ang, Dezhi Zheng, Qianxin Hui, Xinlei Chen, Yang Li, Ning Tang, Effie Chew, Rosary Yuting Lim, Cuntai Guan

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Predicting Return-to-Sport Timeline: Classifying Anterior Cruciate Ligament Health Levels Post-Reconstruction Surgery Using Convolutional Neural Networks by Zeinab Jafari, Ali Sharifnezhad, Mohammad Razi, Mohammad Haghpanahi, Arash Maghsoudi

“…We defined three ACL health levels: healthy, six months post-ACLR, and nine months post-ACLR. Surface electromyography (sEMG) signals were recorded from five knee muscles during single-leg drop landing (SLDL) and single-leg forward hopping (SLFH) tasks. …”
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YOLOv8 with Post-Processing for Small Object Detection Enhancement by Jinkyu Ryu, Dongkurl Kwak, Seungmin Choi

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Toward Reliable Post-Disaster Assessment: Advancing Building Damage Detection Using You Only Look Once Convolutional Neural Network and Satellite Imagery by César Luis Moreno González, Germán A. Montoya, Carlos Lozano Garzón

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Multi-Scale Self-Attention-Based Convolutional-Neural-Network Post-Filtering for AV1 Codec: Towards Enhanced Visual Quality and Overall Coding Performance by Woowoen Gwun, Kiho Choi, Gwang Hoon Park

“…This paper presents MS-MTSA, a multi-scale multi-type self-attention network designed to enhance AV1-compressed video through targeted post-filtering. The objective is to address two persistent artifact issues observed in our previous MTSA model: visible seams at patch boundaries and grid-like distortions from upsampling. …”
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A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection by Noppadol Maneerat, Athasart Narkthewan, Kazuhiko Hamamoto

“…Tuberculosis (TB) is the most serious worldwide infectious disease and the leading cause of death among people with HIV. …”
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GHMSA-Net: Gated Hierarchical Multi-Scale Self-Attention for Perceptually-Guided AV1 Post-Processing by Bopu Zhao, Woowoen Gwun, Kiho Choi

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Evaluation of Post Hoc Uncertainty Quantification Approaches for Flood Detection From SAR Imagery by Jakob Ludwig, Ronny Hansch

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Identifying Forest Burned Area Using a Deep Learning Model Based on Post-Fire Optical and SAR Remote Sensing Images by Xiaofei Xi, Man Kang, Long Dai, Yan Jing, Peng Han, Congqiang Hou

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Fine-art recognition using convolutional transformers by Yu Liu, Haozhe Bai, Jingchao Wang

“…As part of the most advanced architectures in the deep learning family, transformers are empowered by a multi-head attention mechanism, thus improving learning efficiency. …”
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Computing nasalance with MFCCs and Convolutional Neural Networks. by Andrés Lozano, Enrique Nava, María Dolores García Méndez, Ignacio Moreno-Torres

“…Future studies should explore how to optimize mfccNasalance by selecting the most adequate CNN model as a function of the dynamicity of the target speech data.…”
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A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…Soybean yield prediction is one of the most critical activities for increasing agricultural productivity and ensuring food security. …”
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Region‐based fully convolutional networks with deformable convolution and attention fusion for steel surface defect detection in industrial Internet of Things by Meixia Fu, Jiansheng Wu, Qu Wang, Lei Sun, Zhangchao Ma, Chaoyi Zhang, Wanqing Guan, Wei Li, Na Chen, Danshi Wang, Jianquan Wang

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Real-Time Super Resolution Utilizing Dilation and Depthwise Separable Convolution by Che-Cheng Chang, Wen-Pin Chen, Yi-Wei Lin, Yu-Jhan Lin, Po-Jui Pan

“…Therefore, we designed a new dilation depthwise super-resolution (DDSR) model that is composed of dilation convolution, depthwise separable convolution, and residual connection, to overcome the predicaments. …”
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