Paper-Conference

Super-Resolution Benchmarking for 3D Image-to-Image Fusion Problem
Fluorescence microscopy faces challenges in resolution, phototoxicity, and anisotropic artifacts. The Fuse My Cells challenge, …
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Advancing Road Safety: A CNN-Based Semi-Supervised Learning Approach for Drivers' Drowsiness Detection
The National Safety Council (NSC) has reported that each year, driver fatigue is responsible for 100,000 accidents, 71,000 injuries, …
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Data Augmentation Techniques for Medical Image Segmentation - A Review
Segmentation of medical images is crucial for accu-rate diagnosis, treatment planning and intervention. However, the scarcity of data …
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Deep Learning Image-Based Plant Disease Classification - A Review
Effective classification of plant diseases is crucial for increasing agricultural productivity and ensuring global food se-curity. Deep …
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Superpixel Mixing: A Data Augmentation Technique For Robust Deep Visual Recognition Models
Data augmentation can mitigate overfitting problems in data exploration without increasing the size of the model. Existing cutmix-based …
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Enhancing mobile robot surveillance in restricted areas: an optimal visual perception methodology for preventive security
The recent advances in mobile robot surveillance have significantly enhanced supervision tasks. Unlike traditional CCTV systems, these …
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Pixel-Level Quality Indicator for Image Data Annotation
The creation of image classification and segmentation Machine Learning products requires the annotation of different classes by experts …
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Analysis of Point Cloud Domain Gap Effects for 3D Object Detection Evaluation
The development of autonomous driving systems heavily relies on high-quality LiDAR data, which is essential for robust object detection …
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Large Scale Graph Construction and Label Propagation
Despite the advances in semi-supervised learning methods, these algorithms face three limitations. The first is the assumption of …
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Multi-Level XAI-Driven MLOps Pipeline for the Adjustment of Fruit and Vegetable Classifiers
In this paper, we present a machine learning operations (MLOps) pipeline that exploits explainable artificial intelligence (XAI) to …
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