In recent years, weakly supervised semantic segmentation using image-level labels as supervision has received significant attention in the field of computer vision. Most existing methods have addressed the challenges ...
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ISBN:
(纸本)9798350350494;9798350350500
In recent years, weakly supervised semantic segmentation using image-level labels as supervision has received significant attention in the field of computer vision. Most existing methods have addressed the challenges arising from the lack of spatial information in these labels by focusing on facilitating supervised learning through the generation of pseudolabels from class activation maps (CAMs). Due to the localized pattern detection of Convolutional Neural networks (CNNs), CAMs often emphasize only the most discriminative parts of an object, making it challenging to accurately distinguish foreground objects from each other and the background. Recent studies have shown that Vision Transformer (ViT) features, due to their global view, are more effective in capturing the scene layout than CNNs. However, the use of hierarchical ViTs has not been extensively explored in this field. this work explores the use of Swin Transformer by proposing "SWTformer" to enhance the accuracy of the initial seed CAMs by bringing local and global views together. SWTformer-V1 generates class probabilities and CAMs using only the patch tokens as features. SWTformer-V2 incorporates a multi-scale feature fusion mechanism to extract additional information and utilizes a background-aware mechanism to generate more accurate localization maps with improved cross-object discrimination. Based on experiments on the PascalVOC 2012 dataset, SWTformer-V1 achieves a 0.98% mAP higher localization accuracy, outperforming state-of-the-art models. It also yields comparable performance by 0.82% mIoU on average higher than other methods in generating initial localization maps, depending only on the classification network. SWTformer-V2 further improves the accuracy of the generated seed CAMs by 5.32% mIoU, further proving the effectiveness of the local-to-global view provided by the Swin transformer. Code available at: https://***/RozhanAhmadi/SWTformer
Road surface conditions significantly impact traffic flow, vehicle integrity, and driver safety. this importance is magnified in the context of service vehicles, where speed is often the only recourse for saving lives...
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In this paper, we propose two additional heatmap constraint methods that can be integrated into existing detection-based 3D Hand Pose Estimation backbone networks. Our methods effectively reduce the gap between the tr...
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Social media has transformed into a prominent hub for cyberbullying, particularly impacting the younger demographic. the surge in social networking platforms has led to a corresponding increase in instances of online ...
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Aspect-Based Sentiment Analysis (ABSA) is a finegrained sub-task of Natural Language Processing concerned with opinion bearing on certain aspects contained in text. the shift towards multicultural content on the digit...
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Withthe wide application of deep neural networks, the security problem of the model is becoming more prominent, adversarial attack is an important tool for evaluating the robustness and security of the model, adversa...
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ISBN:
(纸本)9798350349184;9798350349191
Withthe wide application of deep neural networks, the security problem of the model is becoming more prominent, adversarial attack is an important tool for evaluating the robustness and security of the model, adversarial attack can be categorized into white-box and black-box attacks. Aiming at the problem of huge perturbation and the low success rate of the adversarial example created in the transfer attack in the black box, a local region approach for randomly segmented channels is given. By randomly segmenting individual dimensions in order to improve the transferability of the adversarial example, the ScoreCAM method is introduced to extract localized focus regions of the image to generate the adversarial example. Experiments show that the performance of the method is better than the baseline algorithm;the fooling rate improved by up to 17%;and the average 2-norm module length decreased by 54.2%.
the paper is devoted to construction the special the software complex for analysis, synthesis and modeling of the control system for marine vessels. the complex is designed in MATLAB-Simulink package. It contains math...
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ISBN:
(纸本)9783031705175;9783031705182
the paper is devoted to construction the special the software complex for analysis, synthesis and modeling of the control system for marine vessels. the complex is designed in MATLAB-Simulink package. It contains mathematical and computer model of the controlled object, mathematical and computer model of controller and tools for visualization. this software complex is universal for all objects with similar mathematical model and it can be easily modified for any marine vessel. In the paper the structure of software complex is given. Its work is illustrated by an example of real vessel #CSOC1120.
Software Defined Networking is a new technology that redefines the architecture of computernetworks and overcomes the several limitations of Traditional networks by decoupling the control and data plane. SDN has draw...
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the proceedings contain 119 papers. the topics discussed include: automatic accident detection system using IoT compared to the systems that a traffic center uses for accident detection;usability evaluation of handhel...
the proceedings contain 119 papers. the topics discussed include: automatic accident detection system using IoT compared to the systems that a traffic center uses for accident detection;usability evaluation of handheld and wearable AR devices: exploring collaboration and the role of physical props;an improved hybrid metaheuristic for active job-shop scheduling problems;machine learning for predicting energy efficiency of buildings: a small data approach;digital citizenship and sustainable governance: a design thinking approach;time pressure's impact on taxi drivers' driving speed: a driving simulator study;exploring driver behaviors during tailgating situations: a driving simulator study;information system for remediation and cleanup of contaminated soil with machine learning;and from raw data to informed decisions: the development of an online data repository and visualization dashboard for transportation data.
Flying ad hoc networks (FANET) are defined by their energetic topology and the absence of fixed infrastructure, which makes efficient routing an important challenge. Traditional routing protocols faced an indeed impos...
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