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Generating Sub-emotions from Social Media Data Using NLP to Ascertain Mental Illness
It is predicted that mental illness will be one of the leading causes of death in 2030. Many people will not share their details of the illness...
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Instance Segmentation Applied to Underground Infrastructures
As underground infrastructures suffer from strikes during the ground excavation procedure resulting from poor subsurface utilities documentation,...
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Pain and Fear in the Eyes: Gaze Dynamics Predicts Social Anxiety from Fear Generalisation
This study presents a systematic approach for analyzing eye movements in the context of fear generalisation and predicting Social Interaction Anxiety...
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Assessing Machine Learning Algorithms for Land Use and Land Cover Classification in Morocco Using Google Earth Engine
Google Earth Engine constitutes a cloud-based geospatial data processing platform. It grants free access to vast volumes of satellite data along with...
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On-Device Learning with Binary Neural Networks
Existing Continual Learning (CL) solutions only partially address the constraints on power, memory and computation of the deep learning models when...
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Towards One-Shot PCB Component Detection with YOLO
Consumer electronic devices such as smartphones, TV sets, etc. are designed around printed circuit boards (PCBs) with a large number of surface...
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Automated Identification of Failure Cases in Organ at Risk Segmentation Using Distance Metrics: A Study on CT Data
Automated organ at risk (OAR) segmentation is crucial for radiation therapy planning in CT scans, but the generated contours by automated models can...
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A General Purpose Method for Image Collection Summarization and Exploration
We propose a flexible framework that can be used to explore large-scale image datasets and summarize photo albums. Our proposed method first groups...
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Generating Invariance-Based Adversarial Examples: Bringing Humans Back into the Loop
One of the major challenges in computer vision today is to align human and computer vision. Using an adversarial machine learning perspective, we...
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Autonomous Agent Using AI Q-Learning in Augmented Reality Ludo Board Game
An autonomous agent works with Artificial Intelligence (AI) can decide its actions to adapt and respond to the changes in a dynamic environment. The...
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FeDZIO: Decentralized Federated Knowledge Distillation on Edge Devices
In recent years, the proliferation of edge devices and distributed sensors has fueled the need for training sophisticated deep learning models...
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GeomEthics: Ethical Considerations About Using Artificial Intelligence in Geomatics
Artificial intelligence (AI) has made significant advancements in the field of geomatics, revolutionizing the way geospatial data is processed,...
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Feature Relevance in Classification of 3D Stone from Ancient Wall Structures
The increasing availability of quantitative data in archaeological studies has prompted the research of Machine Learning methods to support...
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Progressive Keypoint Localization and Refinement in Image Matching
Image matching is the core of many computer vision applications for cultural heritage. The standard image matching pipeline detects keypoints at the...
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Assessing the Robustness and Reproducibility of CT Radiomics Features in Non-small-cell Lung Carcinoma
The aim of this study was to investigate the robustness of radiomics features extracted from computed tomography (CT) images of patients affected by...
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Prediction of High Pathological Grade in Prostate Cancer Patients Undergoing [18F]-PSMA PET/CT: A Preliminary Radiomics Study
The aim of this study was to evaluate the effectiveness of [18F]-prostate-specific membrane antigen (PSMA) positron emission tomography/computed...
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Synthetic Lines from Historical Manuscripts: An Experiment Using GAN and Style Transfer
Given enough data of sufficient quality, HTR systems can achieve high accuracy, regardless of language, script or medium. Despite growing pooling of...
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Classification of Turkish and Balkan House Architectures Using Transfer Learning and Deep Learning
Classifying architectural structures is an important and challenging task that requires expertise. Convolutional Neural Networks (CNN), which are a...
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Examining the Robustness of an Ensemble Learning Model for Credibility Based Fake News Detection
Ensemble learning is a technique of combining multiple base machine learning models and using the blended results as the final classification output....
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