154 Result(s)
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Chapter and Conference Paper
Enhanced Featurization of Queries with Interval Density Encoding
Learning-based cardinality estimation methods outperform traditional methods by effectively overcoming strong assumptions(attribute value independence and uniform distribution). Existing learning-based methods...
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Chapter and Conference Paper
Accelerated Lifetime Experiment of Maximum Current Ratio Based on Charge and Discharge Capacity Confinement
Lithium-ion batteries will undergo continuous aging during the process of charging and discharging. Charging and discharging cycle conditions for lithium-ion batteries are usually an important method to detect...
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Chapter and Conference Paper
Visual Realism Assessment for Face-Swap Videos
Deep-learning-based face-swap videos, also known as deepfakes, are becoming more and more realistic and deceiving. The malicious usage of these face-swap videos has caused wide concerns. The research community...
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Chapter and Conference Paper
Adaptive Rounding Compensation for Post-training Quantization
Network quantization can compress and accelerate deep neural networks by reducing the bit-width of network parameters so that the quantized networks can be deployed to resource-limited devices. Post-Training Q...
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Chapter and Conference Paper
Learning a Deep Fourier Attention Generative Adversarial Network for Light Field Image Super-Resolution
Human eyes can see the three-dimensional (3D) world because they receive the light emitted by objects, and the light field (LF) is a complete representation of the set of light in the 3D world. Light field ima...
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Chapter and Conference Paper
Training Noise Robust Deep Neural Networks with Self-supervised Learning
Training accurate deep neural networks (DNNs) on datasets with label noise is challenging for practical applications. The sample selection paradigm is a popular strategy that selects potentially clean data fro...
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Chapter and Conference Paper
Multi-modal Multi-emotion Emotional Support Conversation
This paper proposes a new task of Multi-modal Multi-emotion Emotional Support Conversation (MMESC), which has great value in various applications, such as counseling, daily chatting, and elderly company. This tas...
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Chapter and Conference Paper
RLMixer: A Reinforcement Learning Approach for Integrated Ranking with Contrastive User Preference Modeling
There is a strong need for industrial recommender systems to output an integrated ranking of items from different categories, such as video and news, to maximize overall user satisfaction. Integrated ranking f...
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Chapter and Conference Paper
Text-Aware Single Image Specular Highlight Removal
Removing undesirable specular highlight from a single input image is of crucial importance to many computer vision and graphics tasks. Existing methods typically remove specular highlight for medical images an...
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Chapter and Conference Paper
Reciprocal Learning for Semi-supervised Segmentation
Semi-supervised learning has been recently employed to solve problems from medical image segmentation due to challenges in acquiring sufficient manual annotations, which is an important prerequisite for buildi...
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Chapter and Conference Paper
A Novel Autonomous Molecular Mechanism Based on Spatially Localized DNA Computation
Contemporary DNA synthesis technology matures, and the development provides intriguing possibilities for dynamic manipulation of DNA self-assembly, which plays a pivotal role in the behavior of designing versa...
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Chapter and Conference Paper
Triplet-Branch Network with Prior-Knowledge Embedding for Fatigue Fracture Grading
In recent years, there has been increasing awareness of the occurrence of fatigue fractures. Athletes and soldiers, who engaged in unaccustomed, repetitive or vigorous activities, are potential victims of such...
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Chapter and Conference Paper
EEG Characteristic Investigation of the Sixth-Finger Motor Imagery
Supernumerary Robotic Limbs (SRL) are body augmentation robotic devices by adding extra limbs or fingers to the human body different from the traditional wearable robotic devices such as prosthesis and exoskel...
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Chapter and Conference Paper
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound
Standard plane recognition plays an important role in prenatal ultrasound (US) screening. Automatically recognizing the standard plane along with the corresponding anatomical structures in US image can not onl...
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Chapter and Conference Paper
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
Building robust deep learning-based models requires diverse training data, ideally from several sources. However, these datasets cannot be combined easily because of patient privacy concerns or regulatory hurd...
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Chapter and Conference Paper
Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation
Segmentation of whole slide images (WSIs) is an important step for computer-aided cancer diagnosis. However, due to the gigapixel dimension, WSIs are usually cropped into patches for analysis. Processing high-...
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Chapter and Conference Paper
Transfer Learning - Based Intention Recognition of Human Upper Limb in Human - Robot Collaboration
Under the wave of rapid industrial development, automated production is gradually shifting to intelligent and customized production. The human-robot collaboration (HRC) system, as an effective way to improve t...
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Chapter and Conference Paper
Frequency Attention Network: Blind Noise Removal for Real Images
With outstanding feature extraction capabilities, deep convolutional neural networks (CNNs) have achieved extraordinary improvements in image denoising tasks. However, because of the difference of statistical ...
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Chapter and Conference Paper
An SMA Inchworm-Imitated Robot for Confined Space Inspection
Machines with complicated inner structures are dominating daily life with its diverse functions and high integration. With the increasing disassembling-assembling difficulty, the in-situ inspection and repairi...
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Chapter and Conference Paper
Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation
Computed tomography (CT) reconstruction from X-ray projections acquired within a limited angle range is challenging, especially when the angle range is extremely small. Both analytical and iterative models nee...