Journals starting with fade

FaDE-TCV22 * *Fair, Data-Efficient and Trusted Computer Vision
* Class-wise Thresholding for Robust Out-of-Distribution Detection
* Color Invariant Skin Segmentation
* DeSI: Deepfake Source Identifier for Social Media
* Doppelgänger Saliency: Towards More Ethical Person Re-Identification
* Epistemic Uncertainty-Weighted Loss for Visual Bias Mitigation
* Examination of Bias of Facial Analysis based BMI Prediction Models, An
* Is Neuron Coverage Needed to Make Person Detection More Robust?
* medXGAN: Visual Explanations for Medical Classifiers through a Generative Latent Space
* OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis
* Pyramidal Attention for Saliency Detection
* Segmenting across places: The need for fair transfer learning with satellite imagery
* Visual Domain Bridge: A source-free domain adaptation for cross-domain few-shot learning
13 for FaDE-TCV22

FaDE-TCV23 * *Fair, Data-Efficient and Trusted Computer Vision
* Casual Conversations v2 Dataset: A diverse, large benchmark for measuring fairness and robustness in audio/vision/speech models, The
* Estimating and Maximizing Mutual Information for Knowledge Distillation
* Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attention
* Learning unbiased classifiers from biased data with meta-learning
* MMRNet: Improving Reliability for Multimodal Object Detection and Segmentation for Bin Picking via Multimodal Redundancy
* Robustness Against Gradient based Attacks through Cost Effective Network Fine-Tuning
* Schrödinger's Camera: First Steps Towards a Quantum-Based Privacy Preserving Camera
* Synthetic Sample Selection for Generalized Zero-Shot Learning
9 for FaDE-TCV23

FaDE-TCV24 * *Fair, Data-Efficient and Trusted Computer Vision
* AR-CP: Uncertainty-Aware Perception in Adverse Conditions with Conformal Prediction and Augmented Reality For Assisted Driving
* Data-free Defense of Black Box Models Against Adversarial Attacks
* DIA: Diffusion based Inverse Network Attack on Collaborative Inference
* Enforcing Conditional Independence for Fair Representation Learning and Causal Image Generation
* Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models
* Fractals as Pre-training Datasets for Anomaly Detection and Localization
* Improving the Robustness of 3D Human Pose Estimation: A Benchmark Dataset and Learning from Noisy Input
* Mitigating Bias Using Model-Agnostic Data Attribution
* Our Deep CNN Face Matchers Have Developed Achromatopsia
* Practical Region-level Attack against Segment Anything Models
* ReweightOOD: Loss Reweighting for Distance-based OOD Detection
* RLNet: Robust Linearized Networks for Efficient Private Inference
* Robust and Explainable Fine-Grained Visual Classification with Transfer Learning: A Dual-Carriageway Framework
* SkipPLUS: Skip the First Few Layers to Better Explain Vision Transformers
* T2FNorm: Train-time Feature Normalization for OOD Detection in Image Classification
* Test-time Assessment of a Model's Performance on Unseen Domains via Optimal Transport
* Towards Efficient Machine Unlearning with Data Augmentation: Guided Loss-Increasing (GLI) to Prevent the Catastrophic Model Utility Drop
* Towards Explainable Visual Vessel Recognition Using Fine-Grained Classification and Image Retrieval
19 for FaDE-TCV24

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