By Plamen Angelov, Yannis Manolopoulos, Lazaros Iliadis, Asim Roy, Marley Vellasco
The booklet bargains a well timed image of neural community applied sciences as an important part of mammoth information analytics systems. It promotes new advances and examine instructions in effective and leading edge algorithmic methods to studying significant facts (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on diverse computing structures (e.g. neuromorphic, pictures processing devices (GPUs), clouds, clusters); and large facts analytics functions to unravel real-world difficulties (e.g. climate prediction, transportation, power management). The booklet, which reviews at the moment version of the hotels convention on significant information, hung on October 23–25, 2016, in Thessaloniki, Greece, depicts a fascinating collaborative event of neural networks with monstrous info and different studying technologies.
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Extra info for Advances in Big Data: Proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece
Org/. r. html. 15 k-means (k) 4 5 6 7 8 9 10 12 14 16 19 Approximate k-means (k) Visual Vocabulary Construction Image Clustering clusters Fig. 3. The hybrid visual vocabulary construction framework using the DBSCANMartingale for the estimation of k and either exact or approximate k-means clustering by k. After the visual vocabulary is constructed, the collection of images is eﬃciently represented for any application, such as image retrieval or clustering. 5 Experiments We evaluate our method in the image retrieval and image clustering tasks, in which nearest neighbor search is performed in an unsupervised way.
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