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Found 12 papers, 3 papers with code
Feature CAM: Interpretable AI in Image Classification
We then extend the same for eight CNN-based architectures to compare the differences in visualization and thus interpretability.
TaE: Task-aware Expandable Representation for Long Tail Class Incremental Learning
Existing methods mainly focus on preserving representative samples from previous classes to combat catastrophic forgetting.
3D Pose Estimation and Future Motion Prediction from 2D Images
This paper considers to jointly tackle the highly correlated tasks of estimating 3D human body poses and predicting future 3D motions from RGB image sequences.
Toward Annotator Group Bias in Crowdsourcing
We conduct experiments on both synthetic and real-world datasets.
Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry
To mathematically prove this, we borrow a tool in topological algebra: Betti numbers to measure the topological geometric complexity of input data and the neural network.
Object Wake-up: 3D Object Rigging from a Single Image
A dataset of generic 3D objects with ground-truth annotated skeletons is collected.
Molecular Clouds in the Second Quadrant of the Milky Way Mid-plane from l$=$104$.\!\!^{\circ}$75 to l=119$.\!\!^{\circ}$75 and b=$-$5$.\!\!^{\circ}$25 to b=5$.\!\!^{\circ}$25
About 78\% of the N-PDFs of the selected molecular clouds are well fitted with log-normal functions with only small deviations at high-densities which correspond to star-forming regions with scales of $\sim$1-5 pc in the Local arm and $\sim$5-10 pc in the Perseus arm.
Astrophysics of Galaxies
Distances to molecular clouds in the second Galactic quadrant
We present distances to 76 medium-sized molecular clouds and an extra large-scale one in the second Galactic quadrant ($104. 75^\circ <l<150. 25^\circ $ and $|b|<5. 25^\circ$), 73 of which are accurately measured for the first time.
Astrophysics of Galaxies
Cuid: A new study of perceived image quality and its subjective assessment
It is thus critical to acquire reliable subjective data with controlled perception experiments that faithfully reflect human behavioural responses to distortions in visual signals.
Sampling-Bias-Corrected Neural Modeling for Large Corpus Item Recommendations
However, batch loss is subject to sampling bias which could severely restrict model performance, particularly in the case of power-law distribution.
IVUS-Net: An Intravascular Ultrasound Segmentation Network
IntraVascular UltraSound (IVUS) is one of the most effective imaging modalities that provides assistance to experts in order to diagnose and treat cardiovascular diseases.
Geodesic Distance Function Learning via Heat Flow on Vector Fields
Based on our theoretical analysis, we propose to first learn the gradient field of the distance function and then learn the distance function itself.
