(A) Object detection task. Left column: full code (red) optimized for image reconstruction; right column: adaptive code (blue) for inference. Top row: uncertainty vs. population activity; bottom row: uncertainty vs. representation accuracy. Each scatter density plot displays 10,000 points. Red, dashed lines depict the linear fit. (B) Same as (A) but for the orientation estimation task. (TIF)</p
The file contains accuracy estimates of binarization algorithms of hemispherical photographs. Column...
The left most column shows the image presented. The second column in each row names the object from ...
This work focuses on comparing three widely used methods for improving uncertainty estimations: Deep...
(A) Rows correspond to inference tasks: object detection (top), target localization (middle), and or...
(A) Rows correspond to inference tasks: object detection (top), target localization (middle), and or...
(A) Rows correspond to inference tasks: object detection (top), target localization (middle), and or...
(A) Rows correspond to individual inference tasks: object detection (top), target localization (midd...
<p>Plots are the histograms of the pooled subject data for each task type (by row) and uncertainty l...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
(A) Object detection task. Top: time course of posterior uncertainty (in bits) averaged over 500 swi...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
<p>A. Classification model fot target detection built from the Color Luminance experiment and used t...
<div> <div> <div> <p>Estimated population distributions for human performance on the Category Chain....
Handling classification uncertainty is crucial for supporting efficient and ethical classification s...
<p>The left column shows model observers' response distributions given input and values 6.0 and 3....
The file contains accuracy estimates of binarization algorithms of hemispherical photographs. Column...
The left most column shows the image presented. The second column in each row names the object from ...
This work focuses on comparing three widely used methods for improving uncertainty estimations: Deep...
(A) Rows correspond to inference tasks: object detection (top), target localization (middle), and or...
(A) Rows correspond to inference tasks: object detection (top), target localization (middle), and or...
(A) Rows correspond to inference tasks: object detection (top), target localization (middle), and or...
(A) Rows correspond to individual inference tasks: object detection (top), target localization (midd...
<p>Plots are the histograms of the pooled subject data for each task type (by row) and uncertainty l...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
(A) Object detection task. Top: time course of posterior uncertainty (in bits) averaged over 500 swi...
Each row represents a complete analysis for a single subject. Columns represent different levels of ...
<p>A. Classification model fot target detection built from the Color Luminance experiment and used t...
<div> <div> <div> <p>Estimated population distributions for human performance on the Category Chain....
Handling classification uncertainty is crucial for supporting efficient and ethical classification s...
<p>The left column shows model observers' response distributions given input and values 6.0 and 3....
The file contains accuracy estimates of binarization algorithms of hemispherical photographs. Column...
The left most column shows the image presented. The second column in each row names the object from ...
This work focuses on comparing three widely used methods for improving uncertainty estimations: Deep...