Lightweight semantic segmentation network
WebJan 1, 2024 · Hyojin Park [ 6] also proposed an extremely lightweight portrait segmentation network-SINet, which is based on [ 21] and achieved higher segmentation accuracy than [ 20 ]. 3 Our Methods In this section, we explained the network structure of … Weblightweight real-time semantic segmentation remote sensing image deep learning Disclosure statement No potential conflict of interest was reported by the author (s). Data Availability The data and the code of this study are available from the corresponding author upon request. ([email protected]) Additional information Funding
Lightweight semantic segmentation network
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WebApr 7, 2024 · 作者：Xiaohang Zhan,Ziwei Liu,Ping Luo,Xiaoou Tang,Chen Change Loy 摘要：Deep convolutional networks for semantic image segmentation typically require large-scale labeled data, e.g. ImageNet and MS COCO, for network pre-training. To reduce annotation efforts, self-supervised semantic segmentation is recently proposed to pre … WebJul 27, 2024 · A Lightweight Semantic Segmentation Algorithm Based on Deep Convolutional Neural Networks Computational Intelligence and Neuroscience / 2024 / Article Special Issue Multidimensional Cognitive …
WebSep 17, 2024 · In this paper, a lightweight feature reuse network MHANet for real-time semantic segmentation is proposed. The main novelties of our method are improved ResNet and attention-based fusion mechanism. WebApr 15, 2024 · However, mobile tongue image segmentation is challenging on account of low-quality image and limited computing power. In this paper, we propose a deep semantic enhanced (DSE) network to address ...
WebMay 10, 2024 · (CGNet) A Light-weight Context Guided Network for Semantic Segmentation (Fast-SCNN) Fast Semantic Segmentation Network (DABNet) Depth-wise Asymmetric … WebJul 8, 2024 · In this paper, we propose LessNet, a lightweight and efficient voxel-based method for LiDAR-only semantic segmentation, taking advantage of cylindrical partition …
WebNov 12, 2024 · The image semantic segmentation method based on CNN can separate the foreground and background in an image by training the full convolution neural network …
WebOct 13, 2024 · Semantic segmentation of remote sensing images plays a crucial role in urban planning and development. How to perform automatic, fast, and effective semantic segmentation of considerable size and high-resolution remote sensing images has become the key to research. However, the existing segmentation methods based on deep learning … spotlight search macWebApr 15, 2024 · To address these issues, we propose DSE-Net to achieve the goal of fast and accurate tongue segmentation on mobile devices. DSE-Net is composed of three parts including encoder, DSE module and decoder. The feature extractor is lightweight and can accommodate the memory requirements of mobile devices. spotlights ebayWebIn this paper, we propose a light-weighted real-time smoke segmentation network to solve the challenging task of smoke semantic segmentation on mobile or computation limited … spotlights eventsWebThis paper proposes a novel, lightweight deep convolutional neural network specifically designed for iris segmentation of noisy images acquired by mobile devices. Unlike previous studies, which only focused on improving the accuracy of segmentation mask using the popular CNN technology, our method is a complete end-to-end iris segmentation solution, … sheng0208WebApr 14, 2024 · Thus, we propose a novel lightweight neural network, named TasselLFANet, with an efficient and powerful structure for accurately and efficiently detecting and … spotlight sewing machineWebMay 13, 2024 · Abstract: Due to real-time image semantic segmentation needs on power constrained edge devices, there has been an increasing desire to design lightweight semantic segmentation neural network, to simultaneously reduce computational cost and increase inference speed. In this paper, we propose an efficient asymmetric dilated … spotlight search in macWebDec 1, 2024 · In recent years, significant progress has been made in semantic segmentation methods. Traditional semantic segmentation methods based on convolutional neural network (CNN) are prone to lose spatial information in the feature extraction stage, and pay less attention to global context information, especially in some lightweight real-time … sheng14