Locating Target Regions for Image Retrieval in an Unsupervised Manner.

Image retrieval performance can be improved by training a convolutional neural network (CNN) model with annotated data to facilitate accurate localization of target regions. However, obtaining sufficiently annotated data is expensive and impractical in real settings. It is challenging to achieve accurate localization of target regions in an unsupervised manner.

Diagnosis of Alzheimer's Disease Based on Deeply-Fused Nets.

Aim And Objective: Fast and accurate diagnosis of Alzheimer's disease is very important for the care and further treatment of patients. Along with the development of deep learning, impressive progress has also been made in the automatic diagnosis of AD. Most existing studies on automatic diagnosis are concerned with a single base network, whose accuracy for disease diagnosis still needs to be improved.

Characterization and performance of immobilized amylase and cellulase.

The performance of cellulase and amylase immobilized on siliceous supports was investigated. Enzyme uptake onto the support depended on the enzyme source and immobilization conditions. For amylase, the uptake ranged between 20 and 60%, and for cellulase, 7-10%.