Specificity comparison of DDcGAN-GSOM with prevailing methods. حسب Nanavath Kiran Singh Nayak (22184565)

الموضوعات:

Discriminator loss of suggested technique. حسب Nanavath Kiran Singh Nayak (22184565)

الموضوعات:

Comprehensive comparison of state-of-the-art approaches. حسب Nanavath Kiran Singh Nayak (22184565)

الموضوعات:

Energy consumption analysis of DDcGAN-GSOM with existing methods. حسب Nanavath Kiran Singh Nayak (22184565)

الموضوعات:

Analysis of DDcGAN-GSOM delay with existing techniques. حسب Nanavath Kiran Singh Nayak (22184565)

الموضوعات:

Comparative analysis of DDcGAN-GSOM’s Energy Consumption, Throughput, and Dealy. حسب Nanavath Kiran Singh Nayak (22184565)

الموضوعات:

System model of the proposed method. حسب Nanavath Kiran Singh Nayak (22184565)

الموضوعات:

Reducing positional uncertainty حسب He Wu (22584128)

Data_Sheet_1_A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3.pdf حسب Juying Wei (13815403)

DataSheet1_An integrated framework for UAV-based precision plant protection in complex terrain: the ACHAGA solution for multi-tea fields.zip حسب Pengyang Zhang (11256688)

DataSheet3_An integrated framework for UAV-based precision plant protection in complex terrain: the ACHAGA solution for multi-tea fields.zip حسب Pengyang Zhang (11256688)

DataSheet2_An integrated framework for UAV-based precision plant protection in complex terrain: the ACHAGA solution for multi-tea fields.zip حسب Pengyang Zhang (11256688)

DataSheet4_An integrated framework for UAV-based precision plant protection in complex terrain: the ACHAGA solution for multi-tea fields.zip حسب Pengyang Zhang (11256688)

Performance metrics for BrC. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Proposed CVAE model. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Proposed methodology. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Loss vs. Epoch. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Sample images from the BreakHis dataset. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Accuracy vs. Epoch. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"

Segmentation results of the proposed model. حسب Afnan M. Alhassan (18349378)

"…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"