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To maximize network lifetime in Wireless Sensor Networks (WSNs) the paths for data transfer are selected in such a way that the total energy consumed along the path is minimized. To support high scalability and better data aggregation, sensor nodes are often grouped into disjoint, non overlapping subsets called clusters. Clusters create hierarchical WSNs(More)
Prostate tissue characteristics play an important role in predicting the recurrence of prostate cancer. Currently, experienced pathologists manually grade these prostate tissues using the Gleason scoring system, a subjective approach which summarizes the overall progression and aggressiveness of the cancer. Using advanced image processing techniques, Aureon(More)
In this paper we propose a novel detail-enhancing exposure fusion approach using nonlinear translation-variant filter (NTF). With the captured Standard Dynamic Range (SDR) images under different exposure settings, first the fine details are extracted based on guided filter. Next, the base layers (i.e., images obtained from NTF) across all input images are(More)
Building training data is labor-intensive and presents a major obstacle to advancing machine learning technologies such as machine translators, named entity recog-nizers (NER), part-of-speech taggers, etc. Training data are often specialized for a particular language or Natural Language Processing (NLP) task. Knowledge captured by a specific set of training(More)