<p>As the accuracy based on the total count does not indicate precision or recall, performance metrics were recorded for a random subset of 100 images. Negative totals are based on the number of non-overlapping regions within each image that are approximately equal in area to a single wildebeest. From these results: precision , recall .</p
Machine Learning techniques can automatically extract information from a variety of multimedia sourc...
The colours of the heat map correspond to the percentage of classification in each category. The acc...
(A) Response rates for the recognition memory judgment are shown for the object-scene and object-loc...
<p>(A), Confusion matrix of the model performance on the dataset of 15 scenes. The average accuracy ...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Precision is the proportion of submitted identifications which were correct; miss rate is the pro...
<p>Confusion matrix and overall performance of the classifier used to determine the sharpness of the...
<p>The matrix is calculated for the = 24 reference pixels of each of = 16 gray value-strata of a...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
The area of each square represents the value of each matrix entry. Values are counts averaged across...
<p>Recall values are calculated over the rows and precision values over the columns.</p
The mean classification accuracy comparison while using different sizes of visual vocabulary for 15-...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
When applying classifiers in real applications, the data imbalance often occurs when the number of e...
Machine Learning techniques can automatically extract information from a variety of multimedia sourc...
The colours of the heat map correspond to the percentage of classification in each category. The acc...
(A) Response rates for the recognition memory judgment are shown for the object-scene and object-loc...
<p>(A), Confusion matrix of the model performance on the dataset of 15 scenes. The average accuracy ...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
<p>Precision is the proportion of submitted identifications which were correct; miss rate is the pro...
<p>Confusion matrix and overall performance of the classifier used to determine the sharpness of the...
<p>The matrix is calculated for the = 24 reference pixels of each of = 16 gray value-strata of a...
The confusion matrix representing the computed classification accuracy % for the proposed research w...
The area of each square represents the value of each matrix entry. Values are counts averaged across...
<p>Recall values are calculated over the rows and precision values over the columns.</p
The mean classification accuracy comparison while using different sizes of visual vocabulary for 15-...
The correctly classified data is reflected along the diagonal regions. The misclassified is reflecte...
Since each classifier distinguishes between the desired class and every “other” class, the confusion...
When applying classifiers in real applications, the data imbalance often occurs when the number of e...
Machine Learning techniques can automatically extract information from a variety of multimedia sourc...
The colours of the heat map correspond to the percentage of classification in each category. The acc...
(A) Response rates for the recognition memory judgment are shown for the object-scene and object-loc...