Unification of Blockchain and Internet of Things (BIoT): requirements,working model,challenges and future directions

Wireless Networks - The Internet of Things (IoTs) enables coupling of digital and physical objects using worthy communication technologies and introduces a future vision where computing systems,...     

Correction to: An Enhanced Crow Search Inspired Feature Selection Technique for Intrusion Detection Based Wireless Network System

Wireless Personal Communications -     

An Enhanced Crow Search Inspired Feature Selection Technique for Intrusion Detection Based Wireless Network System

Wireless Personal Communications - Recent development of cognitive computing driven evolutionary techniques improve the overall quality of service and user experience in wireless communication...     

Diagnosis of breast cancer based on modern mammography using hybrid transfer learning

Breast cancer is a common cancer in women. Early detection of breast cancer in particular and cancer, in general, can considerably increase the survival rate of women, and it can be much more effective. This paper mainly focuses on the transfer learning process to detect breast cancer. Modified VGG (MVGG) is proposed and implemented on datasets of 2D and 3D images of mammograms. Experimental results showed that the proposed hybrid transfer learning model (a fusion of MVGG and ImageNet) provides an accuracy of 94.3%. On the other hand, only the proposed MVGG architecture provides an accuracy of 89.8%. So, it is precisely stated that the proposed hybrid pre-trained network outperforms other compared Convolutional Neural Networks. The proposed architecture can be considered as an effective tool for radiologists to decrease the false negative and false positive rates. Therefore, the efficiency of mammography analysis will be improved.