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Learning class-agnostic masks with cross-task refinement for weakly supervised semantic segmentation
Weakly supervised semantic segmentation (WSSS) commonly relies on Class Activation Map** (CAM) to produce pseudo semantic labels using image-level...
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A novel self-supervised sentiment classification approach using semantic labeling based on contextual embeddings
Sentiment Analysis (SA) is a domain or context-oriented task since the sentiment words convey different sentiments in various domains. As a result,...
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Semantic Attack on Disassociated Transaction Data
Accessing and sharing information, including personal data, has become easier and faster than ever because of the Internet. Therefore, businesses...
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Semantic-aware entity alignment for low resource language knowledge graph
Entity alignment (EA) is an important technique aiming to find the same real entity between two different source knowledge graphs (KGs). Current...
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DSPformer: discovering semantic parts with token growth and clustering for zero-shot learning
Transformers have achieved success in many computer vision tasks, but their potential in Zero-Shot Learning (ZSL) has yet to be fully explored. In...
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Multi sentence description of complex manipulation action videos
Automatic video description necessitates generating natural language statements that encapsulate the actions, events, and objects within a video. An...
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Semantic-Based Implicit Feature Transform for Few-Shot Classification
Few-shot learning aims to recognize instances from previously unseen classes based on a very limited number of examples. However, models often face...
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Retrieving images with missing regions by fusion of content and semantic features
Deep neural networks with a significant ability to learn and extract image discriminative features make a significant contribution to image retrieval...
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Product discovery utilizing the semantic data model
Most of the existing techniques to product discovery and recommendations rely on syntactic approaches, thus ignoring valuable and specific semantic...
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Incorporating multivariate semantic association graphs into multimodal networks for information extraction from documents
Documents contain abundant information available for managerial decision-making. However, manual methods of screening document information lack...
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ODSPC: deep learning-based 3D object detection using semantic point cloud
Three-dimensional object detection plays a key role in autonomous driving, which becomes extremely challenging in occlusion situations. This paper...
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Semantic segmentation of remote sensing image based on bilateral branch network
Due to the large intra-class differences between the same categories and the scale imbalance between different categories in the remote sensing image...
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Point attention network for point cloud semantic segmentation
We address the point cloud semantic segmentation problem through modeling long-range dependencies based on the self-attention mechanism. Existing...
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Thermal infrared image semantic segmentation for night-time driving scenes based on deep learning
Semantic segmentation of thermal infrared (ThIR) images is challenging because the images considered in this task are highly complex. The...
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Flexible asymmetric convolutional attention network for LiDAR semantic
LiDAR semantic segmentation is an essential task in understanding 3D semantic information. Currently, the most efficient approach to LiDAR data...
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Query based biomedical document retrieval for clinical information access with the semantic similarity
The amount of exploration done for the available medical literature is quite less and at the same time, there is less awareness of information mining...
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Short-Term Semantic Changes in Space-Related Categories in Russian Media Discourse
AbstractThis study is identifies semantic features of space-related topics and continues a major study of the coverage of space-related issues in...
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Achieving Seamless Semantic Interoperability and Enhancing Text Embedding in Healthcare IoT: A Deep Learning Approach with Survey
Achieving semantic interoperability in healthcare is one of the significant challenges in the rapidly expanding healthcare sector. On the other hand,...
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Machine reading comprehension combined with semantic dependency for Chinese zero pronoun resolution
Pronoun-drop is a common phenomenon in Chinese, zero pronoun resolution aims to recover the pronoun and resolve the anaphora antecedent of the...
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A Machine Translation Like Approach to Generate Business Process Model from Textual Description
Modeling is one of the core tasks in Business Process Management (BPM). It represents the most critical step in the BPM life cycle and is considered...
