Papers Weakly-supervised Learning
“Weakly-supervised Learning” 태그가 달린 논문 613편 · 필터 해제
MissionGNN: Hierarchical Multimodal GNN-based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation
In the context of escalating safety concerns across various domains, the tasks of Video Anomaly Detection (VAD) and Video Anomaly Recognition (VAR) have emerged as critically important for applications in intelligent sur…
Anomaly DetectionGraph GenerationGraph Neural NetworkLanguage Modelling+5Mask the Unknown: Assessing Different Strategies to Handle Weak Annotations in the MICCAI2023 Mediastinal Lymph Node Quantification Challenge
Pathological lymph node delineation is crucial in cancer diagnosis, progression assessment, and treatment planning. The MICCAI 2023 Lymph Node Quantification Challenge published the first public dataset for pathological …
SegmentationWeakly-supervised LearningWeakly Supervised Learning of Cortical Surface Reconstruction from Segmentations
Existing learning-based cortical surface reconstruction approaches heavily rely on the supervision of pseudo ground truth (pGT) cortical surfaces for training. Such pGT surfaces are generated by traditional neuroimage pr…
Surface ReconstructionWeakly-supervised LearningModeling Emotional Trajectories in Written Stories Utilizing Transformers and Weakly-Supervised Learning
Telling stories is an integral part of human communication which can evoke emotions and influence the affective states of the audience. Automatically modeling emotional trajectories in stories has thus attracted consider…
Weakly-supervised LearningAdapting Fine-Grained Cross-View Localization to Areas without Fine Ground Truth
Given a ground-level query image and a geo-referenced aerial image that covers the query's local surroundings, fine-grained cross-view localization aims to estimate the location of the ground camera inside the aerial ima…
Weakly-supervised LearningOptimistic Rates for Learning from Label Proportions
We consider a weakly supervised learning problem called Learning from Label Proportions (LLP), where examples are grouped into ``bags'' and only the average label within each bag is revealed to the learner. We study vari…
PAC learningWeakly-supervised LearningRethinking Early-Fusion Strategies for Improved Multispectral Object Detection
Most recent multispectral object detectors employ a two-branch structure to extract features from RGB and thermal images. While the two-branch structure achieves better performance than a single-branch structure, it over…
Knowledge DistillationMultispectral Object Detectionobject-detectionObject Detection+1Self-Contrastive Weakly Supervised Learning Framework for Prognostic Prediction Using Whole Slide Images
We present a pioneering investigation into the application of deep learning techniques to analyze histopathological images for addressing the substantial challenge of automated prognostic prediction. Prognostic predictio…
Contrastive LearningDiagnosticMultiple Instance LearningPrediction+2Learning from True-False Labels via Multi-modal Prompt Retrieving
Weakly supervised learning has recently achieved considerable success in reducing annotation costs and label noise. Unfortunately, existing weakly supervised learning methods are short of ability in generating reliable l…
Weakly-supervised LearningBoosting Medical Image-based Cancer Detection via Text-guided Supervision from Reports
The absence of adequately sufficient expert-level tumor annotations hinders the effectiveness of supervised learning based opportunistic cancer screening on medical imaging. Clinical reports (that are rich in descriptive…
Clinical KnowledgeDescriptiveDiagnosticLanguage Modelling+1Pre-Trained Vision-Language Models as Partial Annotators
Pre-trained vision-language models learn massive data to model unified representations of images and natural languages, which can be widely applied to downstream machine learning tasks. In addition to zero-shot inference…
Contrastive Learningimage-classificationImage ClassificationKnowledge Distillation+2Towards Graph Contrastive Learning: A Survey and Beyond
In recent years, deep learning on graphs has achieved remarkable success in various domains. However, the reliance on annotated graph data remains a significant bottleneck due to its prohibitive cost and time-intensive n…
Contrastive LearningData AugmentationDrug DiscoveryGraph Learning+5Region-level labels in ice charts can produce pixel-level segmentation for Sea Ice types
Fully supervised deep learning approaches have demonstrated impressive accuracy in sea ice classification, but their dependence on high-resolution labels presents a significant challenge due to the difficulty of obtainin…
Weakly-supervised LearningLearning from Partial Label Proportions for Whole Slide Image Segmentation
In this paper, we address the segmentation of tumor subtypes in whole slide images (WSI) by utilizing incomplete label proportions. Specifically, we utilize `partial' label proportions, which give the proportions among t…
DiagnosticImage SegmentationMultiple Instance LearningSemantic Segmentation+2DCNN: Dual Cross-current Neural Networks Realized Using An Interactive Deep Learning Discriminator for Fine-grained Objects
Accurate classification of fine-grained images remains a challenge in backbones based on convolutional operations or self-attention mechanisms. This study proposes novel dual-current neural networks (DCNN), which combine…
Fine-Grained Image Classificationimage-classificationImage ClassificationWeakly-supervised LearningMediFact at MEDIQA-M3G 2024: Medical Question Answering in Dermatology with Multimodal Learning
The MEDIQA-M3G 2024 challenge necessitates novel solutions for Multilingual & Multimodal Medical Answer Generation in dermatology (wai Yim et al., 2024a). This paper addresses the limitations of traditional methods by pr…
Answer GenerationMedical Question AnsweringQuestion AnsweringWeakly-supervised LearningImproving Weakly-Supervised Object Localization Using Adversarial Erasing and Pseudo Label
Weakly-supervised learning approaches have gained significant attention due to their ability to reduce the effort required for human annotations in training neural networks. This paper investigates a framework for weakly…
ObjectObject LocalizationPseudo LabelWeakly-supervised Learning+1Weakly-Supervised Learning via Multi-Lateral Decoder Branching for Tool Segmentation in Robot-Assisted Cardiovascular Catheterization
Robot-assisted catheterization has garnered a good attention for its potentials in treating cardiovascular diseases. However, advancing surgeon-robot collaboration still requires further research, particularly on task-sp…
DecoderSegmentationWeakly-supervised LearningPrimary liver cancer classification from routine tumour biopsy using weakly supervised deep learning
The diagnosis of primary liver cancers (PLCs) can be challenging, especially on biopsies and for combined hepatocellular-cholangiocarcinoma (cHCC-CCA). We automatically classified PLCs on routine-stained biopsies using a…
Cancer ClassificationClusteringDiagnosticWeakly-supervised LearningRAP: Retrieval-Augmented Planner for Adaptive Procedure Planning in Instructional Videos
Procedure Planning in instructional videos entails generating a sequence of action steps based on visual observations of the initial and target states. Despite the rapid progress in this task, there remain several critic…
RelationRetrievalWeakly-supervised Learning