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Development of a vertex finding algorithm using Recurrent Neural Network
Deep learning is a rapidly-evolving technology with the possibility to significantly improve the physics reach of collider experiments. …
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Human-Imperceptible Identification With Learnable Lensless Imaging
Lensless imaging protects visual privacy by capturing heavily blurred images that are imperceptible for humans to recognize the subject …
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Information Extraction from Public Meeting Articles
Public meeting articles are the key to understanding the history of public opinion and public sphere in Australia. Information …
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Anonymous identity sampling and reusable synthesis for sensitive face camouflage
An increasing amount of face images are being captured, shared, or applied in various applications. These images usually contain lots …
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Corpus Construction for Historical Newspapers: A Case Study on Public Meeting Corpus Construction Using OCR Error Correction
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Depthwise spatio-temporal STFT convolutional neural networks for human action recognition
Conventional 3D convolutional neural networks (CNNs) are computationally expensive, memory intensive, prone to overfitting, and most …
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Human--Machine Interfaces Based on Bioelectric Signals: A Narrative Review with a Novel System Proposal
Bioelectric signals such as electromyogram (EMG) and electroencephalogram (EEG) reflect human internal states and intended actions, and …
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Match them up: visually explainable few-shot image classification
Few-shot learning (FSL) approaches, mostly neural network-based, assume that pre-trained knowledge can be obtained from base (seen) …
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The semantic typology of visually grounded paraphrases
Visually grounded paraphrases (VGPs) are different phrasal expressions describing the same visual concept in an image. Previous studies …
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A comparative study of language Transformers for video question answering
With the goal of correctly answering questions about images or videos, visual question answering (VQA) has quickly developed in recent …
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