Papers Image Augmentation
“Image Augmentation” 태그가 달린 논문 338편 · 필터 해제
Empowering Local Agriculture: A Deep Learning-Powered Web System for Identifying Bangladeshi Mango Varieties
Mango variety identification in Bangladesh is challenging because closely related cultivars can have similar visual characteristics and images are often captured under varying real-world conditions. This work presents a …
Image AugmentationFailure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement
Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-scale, high-quality multimodal data that are costly to annotate. Sel…
Visual Question AnsweringImage AugmentationMedDiffuseMix: Preserving Diagnostic Evidence with Saliency-Aware Diffusion Medical Image Data Augmentatio
Limited data availability, class imbalance, and domain variability remain major barriers to reliable medical image classification. Conventional augmentation can improve training diversity but may distort diagnostically i…
Medical Image ClassificationImage AugmentationA welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks
The laser welding full-penetration is of critical importance, as it constitutes one of the fundamental factors in achieving defect-free welded joints. Accurate prediction of the penetration state is therefore essential f…
Self-Supervised LearningContrastive LearningImage AugmentationFew-Shot LearningMaking the Discrete Continuous: Synthetic RAW Augmentations for Fine-Grained Evaluation of Person Detection Performance in Low Light
Real-world deployment of AI vision models is both fueled and limited by the data available for training and testing. Real datasets are sparse and uneven: long-tailed or unbalanced distributions hinder generalization, and…
Pedestrian DetectionImage AugmentationAutonomous DrivingObject DetectionCAD-Free Learning of Spacecraft Pose Estimators via NeRF-Based Augmentations
Spacecraft pose estimation networks require tens of thousands of CAD-rendered images to be trained. This reliance on synthetic CAD data (i) limits applicability to targets with reliable geometry prior, excluding uncooper…
Domain GeneralizationImage AugmentationPose EstimationFlow Matching with Optimized Subclass Priors for Medical Image Augmentation
Rare diseases dominate the diagnostic challenge in medical imaging yet are severely underrepresented in clinical datasets, causing classifiers to fail on exactly the conditions where reliable detection matters most. Gene…
Image AugmentationAtteConDA: Attention-Based Conflict Suppression in Multi-Condition Diffusion Models and Synthetic Data Augmentation
Recent conditional image generation methods can improve controllability by generating images that are faithful to conditions such as sketches, human poses, segmentation maps, and depth. By applying these techniques to im…
Conditional Image GenerationSemantic SegmentationImage AugmentationData AugmentationAnemiaVision: Non-Invasive Anemia Detection via Smartphone Imagery Using EfficientNet-B3 with TrivialAugmentWide, Mixup Augmentation, and Persistent Patient History Management
Anemia affects over one billion people globally and remains severely under-diagnosed in low-resource regions where laboratory blood tests are inaccessible. This paper presents AnemiaVision, an end-to-end web-based system…
Image AugmentationA Resource-Efficient Hybrid CNN-LSTM network for image-based bean leaf disease classification
Accurate and resource-efficient automated diagnosis is a cornerstone of modern agricultural expert systems. While Convolutional Neural Networks (CNNs) have established benchmarks in plant pathology, their ability to capt…
Image AugmentationHybrid Diffusion Model for Breast Ultrasound Image Augmentation
We propose a hybrid diffusion-based augmentation framework to overcome the critical challenge of ultrasound data augmentation in breast ultrasound (BUS) datasets. Unlike conventional diffusion-based augmentations, our ap…
Text-to-Image GenerationImage AugmentationData AugmentationToward High-Fidelity Visual Reconstruction: From EEG-Based Conditioned Generation to Joint-Modal Guided Rebuilding
Human visual reconstruction aims to reconstruct fine-grained visual stimuli based on subject-provided descriptions and corresponding neural signals. As a widely adopted modality, Electroencephalography (EEG) captures ric…
Image AugmentationImage GenerationMaximizing Generalization: The Effect of Different Augmentation Techniques on Lightweight Vision Transformer for Bengali Character Classification
Deep learning models have proven to be highly effective in computer vision, with deep convolutional neural networks achieving impressive results across various computer vision tasks. However, these models rely heavily on…
Image AugmentationData AugmentationVisual Word Sense Disambiguation with CLIP through Dual-Channel Text Prompting and Image Augmentations
Ambiguity poses persistent challenges in natural language understanding for large language models (LLMs). To better understand how lexical ambiguity can be resolved through the visual domain, we develop an interpretable …
Natural Language UnderstandingWord Sense DisambiguationImage AugmentationBeyond Cropping and Rotation: Automated Evolution of Powerful Task-Specific Augmentations with Generative Models
Data augmentation has long been a cornerstone for reducing overfitting in vision models, with methods like AutoAugment automating the design of task-specific augmentations. Recent advances in generative models, such as c…
Image AugmentationFew-Shot LearningData AugmentationSkin Lesion Classification Using a Soft Voting Ensemble of Convolutional Neural Networks
Skin cancer can be identified by dermoscopic examination and ocular inspection, but early detection significantly increases survival chances. Artificial intelligence (AI), using annotated skin images and Convolutional Ne…
Skin Lesion ClassificationSkin Cancer ClassificationImage AugmentationTransfer LearningSkinGenBench: Generative Model and Preprocessing Effects for Synthetic Dermoscopic Augmentation in Melanoma Diagnosis
This work introduces SkinGenBench, a systematic biomedical imaging benchmark that investigates how preprocessing complexity interacts with generative model choice for synthetic dermoscopic image augmentation and downstre…
Image AugmentationData AugmentationGradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations
Developing reliable iris recognition and presentation attack detection methods requires diverse datasets that capture realistic variations in iris features and a wide spectrum of anomalies. Because of the rich texture of…
Image AugmentationImage augmentation with invertible networks in interactive satellite image change detection
This paper devises a novel interactive satellite image change detection algorithm based on active learning. Our framework employs an iterative process that leverages a question-and-answer model. This model queries the or…
Image AugmentationChange DetectionActive LearningDenoised Diffusion for Object-Focused Image Augmentation
Modern agricultural operations increasingly rely on integrated monitoring systems that combine multiple data sources for farm optimization. Aerial drone-based animal health monitoring serves as a key component but faces …
Image AugmentationTransfer LearningData Augmentation