:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gajardo, Joaquin, Volpi, Michele, Onwude, Daniel, Defraeye, Thijs
Format:	Preprint
Published:	2023
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2312.10872
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Weakly Supervised Panoptic Segmentation for Defect-Based Grading of Fresh Produce
by: Knott, Manuel, et al.
Published: (2024)

A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification
by: Marks, Markus, et al.
Published: (2024)

Cropland Mapping using Geospatial Embeddings
by: Zvonkov, Ivan, et al.
Published: (2025)

Weak Labeling for Cropland Mapping in Africa
by: Hacheme, Gilles Quentin, et al.
Published: (2024)

Country-wide, high-resolution monitoring of forest browning with Sentinel-2
by: Biegel, Samantha, et al.
Published: (2026)

TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
by: Kwon, Young D., et al.
Published: (2023)

XFlowMap: Cross-Scale Generalization and Mapping of Massive Origin-Destination Data
by: Guo, Diansheng, et al.
Published: (2026)

Enhancing Self-Supervised Learning for Remote Sensing with Elevation Data: A Case Study with Scarce And High Level Semantic Labels
by: Castaño-Idarraga, Omar A., et al.
Published: (2023)

Generalization Enhancement Strategies to Enable Cross-year Cropland Mapping with Convolutional Neural Networks Trained Using Historical Samples
by: Khallaghi, Sam, et al.
Published: (2024)

PRECISe : Prototype-Reservation for Explainable Classification under Imbalanced and Scarce-Data Settings
by: Ganatra, Vaibhav, et al.
Published: (2024)

Self-Supervised Federated Learning under Data Heterogeneity for Label-Scarce Diatom Classification
by: Tan, Mingkun, et al.
Published: (2026)

Physics-Constrained Denoising Autoencoders for Data-Scarce Wildfire UAV Sensing
by: Ramadan, Abdelrahman, et al.
Published: (2026)

Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation
by: Deshpande, Tanvi, et al.
Published: (2024)

Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes
by: Kebaili, Aghiles, et al.
Published: (2024)

Weakly Supervised Framework Considering Multi-temporal Information for Large-scale Cropland Mapping with Satellite Imagery
by: Wang, Yuze, et al.
Published: (2024)

The Impact of an XAI-Augmented Approach on Binary Classification with Scarce Data
by: Wen, Ximing, et al.
Published: (2024)

QID: Efficient Query-Informed ViTs in Data-Scarce Regimes for OCR-free Visual Document Understanding
by: Le, Binh M., et al.
Published: (2025)

Generation of Training Data from HD Maps in the Lanelet2 Framework
by: Immel, Fabian, et al.
Published: (2024)

Efficient Cross-Country Data Acquisition Strategy for ADAS via Street-View Imagery
by: Wu, Yin, et al.
Published: (2026)

UniMapGen: A Generative Framework for Large-Scale Map Construction from Multi-modal Data
by: Yuan, Yujian, et al.
Published: (2025)

Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection
by: Lee, Saehyung, et al.
Published: (2024)

Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory
by: Kälble, Jonas, et al.
Published: (2024)

Wheat3DGS: In-field 3D Reconstruction, Instance Segmentation and Phenotyping of Wheat Heads with Gaussian Splatting
by: Zhang, Daiwei, et al.
Published: (2025)

Self-supervised learning unveils change in urban housing from street-level images
by: Stalder, Steven, et al.
Published: (2023)

Scaling (Down) CLIP: A Comprehensive Analysis of Data, Architecture, and Training Strategies
by: Li, Zichao, et al.
Published: (2024)

MapNeXt: Revisiting Training and Scaling Practices for Online Vectorized HD Map Construction
by: Li, Toyota
Published: (2024)

CD-TVD: Contrastive Diffusion for 3D Super-Resolution with Scarce High-Resolution Time-Varying Data
by: Bi, Chongke, et al.
Published: (2025)

Topological Inductive Bias fosters Multiple Instance Learning in Data-Scarce Scenarios
by: Kazeminia, Salome, et al.
Published: (2023)

Training Data Attribution: Was Your Model Secretly Trained On Data Created By Mine?
by: Zhang, Likun, et al.
Published: (2024)

Is user feedback always informative? Retrieval Latent Defending for Semi-Supervised Domain Adaptation without Source Data
by: Song, Junha, et al.
Published: (2024)

Predicting Infant Brain Connectivity with Federated Multi-Trajectory GNNs using Scarce Data
by: Pistos, Michalis, et al.
Published: (2024)

Women Sport Actions Dataset for Visual Classification Using Small Scale Training Data
by: Ray, Palash, et al.
Published: (2025)

Localization Is All You Evaluate: Data Leakage in Online Mapping Datasets and How to Fix It
by: Lilja, Adam, et al.
Published: (2023)

Scaling Training Data with Lossy Image Compression
by: Mentzer, Katherine L., et al.
Published: (2024)

What You See is What You Classify: Black Box Attributions
by: Stalder, Steven, et al.
Published: (2022)

Mining Field Data for Tree Species Recognition at Scale
by: Gominski, Dimitri, et al.
Published: (2024)

What could go wrong? Discovering and describing failure modes in computer vision
by: Csurka, Gabriela, et al.
Published: (2024)

3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes
by: Kebaili, Aghiles, et al.
Published: (2024)

Breast Cancer VLMs: Clinically Practical Vision-Language Train-Inference Models
by: Zheng, Shunjie-Fabian, et al.
Published: (2025)

Training for Trustworthy Saliency Maps: Adversarial Training Meets Feature-Map Smoothing
by: Bhusal, Dipkamal, et al.
Published: (2026)