updated 2018-19 final (1)

TECH PULSE 2018-2019
U-Net is a convolutional neural network that was
developed for biomedical image segmentation.
The network is based on the fully convolutional
network and its architecture was modified and
extended to work with fewer training images.
It yields more precise segmentations when compared
to other image segmentation models.
The advantages of U-NET model :
1. Computationally efficient
2. Trainable with a small data-set
3. Trained end-to-end
4. Preferable for bio-medical applications
Conclusion:
Image segmentation is being emerged as a powerful
topic in computer vision.
It is multidisciplinary topic that is being used all over
the world for image analysis.
Many models exist for image segmentation, but U-
NET emerged as the most significant model.
References:
https://en.wikipedia.org/wiki/Image_segmentation
https://towardsdatascience.com/understandingsemantic-segmentation-with-unet-6be4f42d4b47
Cloud Computing in the Banking
Industry
The banking industry is home to a large volume of
consumer data and is always eager to provide the best
services to its customers. In such a scenario, the cloud
computing technology serves as a transformative digital
solution which offers unparalleled levels of security,
agility, and scalability to the banking sector while boosting
its capability to handle consumer data.
16A31A0563
CHAGANTI
AMRUTHA SANDHYA
Strategically implemented cloud computing services allow
banks to utilize resources in a highly flexible and efficient
manner with the help of data analytics, data storage, and
batch processing. Further, the cloud technology also helps
the banking industry to improve revenues, operational
efficiency, and the client servicing department.
U-NET Model: