This paper addresses the limitations of the Contrastive Language-Image Pre-training (CLIP) model's image encoder and proposes a segmentation model WSSS-ECFE with enhanced CLIP feature extraction, aiming to improve...
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Remote sensing object detection has important application value in fields such as environmental monitoring and resource detection and analysis. However, the current universal object detectors are not very effective in...
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Text-based person retrieval (TBPR) is a challenging topic in cross-modal retrieval tasks, aiming to query corresponding person images based on textual descriptions. This task is complicated by noisy correspondences be...
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Recently the analysis of remotely sensed images has played a vital role in various aspects of research. The current researches ignore the unique prior knowledge in remote sensing images and do not consider exploring t...
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Small object detection has important application value in the fields of environmental monitoring, resource detection and analysis, etc. However, the current general object detectors are not very ideal for the detectio...
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This paper addresses the limitations of the Contrastive Language-Image Pre-training (CLIP) model’s image encoder and proposes a segmentation model WSSS-ECFE with enhanced CLIP feature extraction, aiming to improve th...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
This paper addresses the limitations of the Contrastive Language-Image Pre-training (CLIP) model’s image encoder and proposes a segmentation model WSSS-ECFE with enhanced CLIP feature extraction, aiming to improve the performance of the Weakly Supervised Semantic Segmentation (WSSS) task. WSSS-ECFE employs the Enhanced Bottleneck module proposed in this paper and adds dynamic residual connection to improve the model’s processing effect on complex scenes. In terms of implementation, the Enhanced Bottleneck module employs the Swish activation function and the Depthwise Separable Convolution to enhance the feature extraction and segmentation capability of the model, and uses multiple attention mechanisms to further optimize the feature representation and segmentation accuracy. The WSSS task on the public datasets PASCAL VOC 2012 and MS COCO 2014 achieves 82.6% and 56.3% mean intersection over union (mIoU), achieving state-of-the-art performance in models with low resource requirements.
Probabilistic tracking algorithms typically using linear structure to update the learning *** linear structure is not appropriate for long-term robust tracking as the occlusion and other challe
ISBN:
(纸本)9781509053643;9781509053636
Probabilistic tracking algorithms typically using linear structure to update the learning *** linear structure is not appropriate for long-term robust tracking as the occlusion and other challe
In many applications of mobile sensor networks, such as water flow monitoring and disaster rescue, the nodes in the network can move together or separate temporarily. The dynamic network topology makes traditional spa...
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In many applications of mobile sensor networks, such as water flow monitoring and disaster rescue, the nodes in the network can move together or separate temporarily. The dynamic network topology makes traditional spanning-tree-based aggregation algorithms invalid in mobile sensor networks. In this paper, we first present a distributed clustering algorithm which divides mobile sensor nodes into several groups, and then propose two distributed aggregation algorithms, Distance-AGG （Aggregation based on Distance）, and Probability-AGG （Aggregation based on Probability）. Both of these two algorithms conduct an aggregation query in three phases： query dissemination, intra-group aggregation, and inter-group aggregation. These two algorithms are efficient especially in mobile networks. We evaluate the performance of the proposed algorithms in terms of aggregation accuracy, energy efficiency, and query delay through ns-2 simulations. The results show that Distance-AGG and Probability-AGG can obtain higher accuracy with lower transmission and query delay than the existing aggregation algorithms.
This paper proposes a data broadcast strategy for traffic information query. Traffic information query is an important application in VANETs. Real-time traffic information query makes users to select path in a short t...
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Collaborative filtering techniques are widely used in e-commerce systems. However, the rating data are very sparse, which affects prediction accuracy greatly. A time division based collaborative filtering algorithm is...
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