Table 2 BC detection outcomes of CVFBJTL-BCD technique on Histopathological dataset.

From: Enhanced breast cancer diagnosis through integration of computer vision with fusion based joint transfer learning using multi modality medical images

Class

\({\varvec{A}}{\varvec{c}}{\varvec{c}}{{\varvec{u}}}_{{\varvec{y}}}\)

\({\varvec{P}}{\varvec{r}}{\varvec{e}}{{\varvec{c}}}_{{\varvec{n}}}\)

\({\varvec{S}}{\varvec{e}}{\varvec{n}}{{\varvec{s}}}_{{\varvec{y}}}\)

\({\varvec{S}}{\varvec{p}}{\varvec{e}}{{\varvec{c}}}_{{\varvec{y}}}\)

\({{\varvec{F}}1}_{{\varvec{s}}{\varvec{c}}{\varvec{o}}{\varvec{r}}{\varvec{e}}}\)

TRAP (70%)

Benign

97.37

96.50

94.94

98.46

95.71

Malignant

97.37

97.76

98.46

94.94

98.11

Average

97.37

97.13

96.70

96.70

96.91

TESP (30%)

Benign

98.18

98.90

95.21

99.52

97.02

Malignant

98.18

97.87

99.52

95.21

98.69

Average

98.18

98.38

97.37

97.37

97.85