8,442 Result(s)
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Computer Science
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Article
Medical image super-resolution via transformer-based hierarchical encoder–decoder network
Medical image super-resolution (SR) has emerged as an effective means to enhance the resolution of medical images. Nevertheless, many existing methods still face the issue of insufficient representation of hig...
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Aspect-level implicit sentiment analysis model based on semantic wave and knowledge enhancement
Most implicit sentiment sentences in aspect level implicit sentiment analysis lack emotional words, but there are still potential emotional clues. Current research mainly utilizes contextual information and ex...
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Article
3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information
Molecular property prediction, crucial for early drug candidate screening and optimization, has seen advancements with deep learning-based methods. While deep learning-based methods have advanced considerably,...
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Diversified deep hierarchical kernel ensemble regression
Deep ensemble learning models that combine multiple independent deep learning models with multi-layer processing architectures have proven to be effective techniques for improving the accuracy and robustness o...
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Digital human and embodied intelligence for sports science: advancements, opportunities and prospects
This paper presents a comprehensive review of state-of-the-art motion capture techniques for digital human modeling in sports, including traditional optical motion capture systems, wearable sensor capture syst...
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Hard semantic mask strategy for automatic facial action unit recognition with teacher–student model
Facial Action Coding System (FACS) is a widely used technique in affective computing, which defines a series of facial action units (AUs) corresponding to localized regions of the face. Fine-grained feature in...
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UTE-CrackNet: transformer-guided and edge feature extraction U-shaped road crack image segmentation
Cracks in the road surface can cause significant harm. Road crack detection, segmentation, and immediate repair can help reduce the occurrence of risks. Some methods based on convolutional neural networks stil...
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Open AccessRobust and privacy-preserving collaborative training: a comprehensive survey
Increasing numbers of artificial intelligence systems are employing collaborative machine learning techniques, such as federated learning, to build a shared powerful deep model among participants, while keepin...
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Open AccessLearnable differencing center for nighttime depth perception
Depth completion is the task of recovering dense depth map from sparse ones, usually with the help of color images. Existing image guided methods perform well on daytime depth perception self-driving benchmark...
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A BEM-OTFS channel estimation method for high mobility 6G-V2X
Aiming at the problem that existing channel estimation methods are unable to track the channel parameter variations within a single frame under continuous Doppler spread channel (CoDSC) which leads to serious ...
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Open AccessIDaTPA: importance degree based thread partitioning approach in thread level speculation
As an auto-parallelization technique with the level of thread on multi-core, Thread-Level Speculation (TLS) which is also called Speculative Multithreading (SpMT), partitions programs into multiple threads and...
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Semi-hard constraint augmentation of triplet learning to improve image corruption classification
When facing the challenge of image distribution shift and natural corruptions, most of data augmentation methods only consider the diversity of training image to enlarge the data quantity, the hardness quality...
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An improved Tasmanian devil optimization algorithm based on sine-cosine strategy with dynamic weighting factors
In this paper, aiming at the problem that the balance between exploration and exploitation of traditional Tasmanian devil optimization algorithm is unflexible, and easy to fall into local optimum, an improved ...
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Article
DisCO: Portrait Distortion Correction with Perspective-Aware 3D GANs
Close-up facial images captured at short distances often suffer from perspective distortion, resulting in exaggerated facial features and unnatural/unattractive appearances. We propose a simple yet effective m...
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Low-parameter GAN inversion framework based on hypernetwork
In response to the significant parameter overhead in current Generative Adversarial Networks (GAN) inversion methods when balancing high fidelity and editability, we propose a novel lightweight inversion frame...
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Precision in pursuit: a multi-consistency joint approach for infrared anti-UAV tracking
In addition to addressing issues commonly encountered in generic visual object tracking, this task endeavors necessitates co** with the diminutive characteristics of infrared UAV targets, potential discontin...
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Cognitive Tracing Data Trails: Auditing Data Provenance in Discriminative Language Models Using Accumulated Discrepancy Score
The burgeoning practice of unauthorized acquisition and utilization of personal textual data (e.g., social media comments and search histories) by certain entities has become a discernible trend. To uphold dat...
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Multiscale dilated convolution and swin-transformer for small sample gearbox fault diagnosis
Mechanical equipment usually operates in noisy and variable load environments, which presents serious challenges for existing intelligent diagnostic models. In addition, there are few labelled fault samples in...
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Open AccessThe network of sports: using network analysis to understand the relationship between sports and socio-physiological factors in contemporary China
This study examines sports and physical activities among Chinese aged 18–65, using network analysis on a significant random sample. It categorizes sports into 11 groups based on public selection, with a commun...
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Article
Utilization of pre-trained language models for adapter-based knowledge transfer in software engineering
Software Engineering (SE) Pre-trained Language Models (PLMs), such as CodeBERT, are pre-trained on large code corpora, and their learned knowledge has shown success in transferring into downstream tasks (e.g.,...
