Neurons exhibit concept-conditioned activation ranges forming Gaussian-like distributions with minimal overlap, and range-based interventions via NeuronLens outperform neuron-level masking in targeted manipulation with reduced collateral effects.
In: 2021 IEEE International Conference on Image Processing (ICIP)
7 Pith papers cite this work, alongside 92 external citations. Polarity classification is still indexing.
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UNVERDICTED 7representative citing papers
Introduces DFHR task, DFHR-Bench with over 180K triplets, and MFHC framework for mixed-modality dual face-hair retrieval.
UHD-GCN-BIQA models structural dependencies among sampled patches via a hybrid kNN graph and residual graph convolutions to achieve competitive PLCC and SRCC with the lowest RMSE on the UHD-IQA benchmark for blind ultra-high-definition image quality assessment.
A neural network trained on full-reference perceptual quality labels predicts minimal sufficient resolution for rendered video to enable power-efficient client-side rendering.
IDCL adds density-based curriculum learning and density-core guidance to deep image clustering, claiming superior robustness, faster convergence, and flexibility on benchmark datasets.
A literature review and industry survey on SDV security and privacy produces a framework for addressing mixed-criticality systems, layered defenses, privacy techniques, and harmonized vehicle-cloud protections.
A survey that categorizes deep learning models for point cloud tasks by backbone architecture, evaluates benchmark performance, and outlines challenges and future research directions.
citing papers explorer
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Neurons Speak in Ranges: Breaking Free from Discrete Neuronal Attribution
Neurons exhibit concept-conditioned activation ranges forming Gaussian-like distributions with minimal overlap, and range-based interventions via NeuronLens outperform neuron-level masking in targeted manipulation with reduced collateral effects.
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Mixed-Modality Dual Face-Hair Retrieval
Introduces DFHR task, DFHR-Bench with over 180K triplets, and MFHC framework for mixed-modality dual face-hair retrieval.
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Ultra-High-Definition Image Quality Assessment via Graph Representation Learning
UHD-GCN-BIQA models structural dependencies among sampled patches via a hybrid kNN graph and residual graph convolutions to achieve competitive PLCC and SRCC with the lowest RMSE on the UHD-IQA benchmark for blind ultra-high-definition image quality assessment.
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Seeing enough: non-reference perceptual resolution selection for power-efficient client-side rendering
A neural network trained on full-reference perceptual quality labels predicts minimal sufficient resolution for rendered video to enable power-efficient client-side rendering.
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Deep Image Clustering Based on Curriculum Learning and Density Information
IDCL adds density-based curriculum learning and density-core guidance to deep image clustering, claiming superior robustness, faster convergence, and flexibility on benchmark datasets.
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Contextualizing Security and Privacy of Software-Defined Vehicles: A Literature Review and Industry Perspectives
A literature review and industry survey on SDV security and privacy produces a framework for addressing mixed-criticality systems, layered defenses, privacy techniques, and harmonized vehicle-cloud protections.
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A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation
A survey that categorizes deep learning models for point cloud tasks by backbone architecture, evaluates benchmark performance, and outlines challenges and future research directions.