We describe a method for construction of specific types of Neural Networks composed of structures directly linked to the structure of the molecule under consideration. Each molecule can be represented by a unique neural connectivity problem (graph) which can be programmed onto a Cellular Neural Network. The idea was to translate chemical structures like small organic molecules or peptides into ...

In this paper, we present a simple yet powerful deep neural network for natural image dehazing. The proposed method is designed based on U-Net architecture and made some design changes to make it better. We first use Group Normalization replace Batch solve the problem of insufficient batch size due hardware limitations. Second, introduce FReLU activation into block, which can achieve capturing ...

ProjectH, a research group of a hundred researchers, produced a huge amount of data from computer mediated discussions. The data classi ed several thousand postings from over 30 newsgroups into 46 categories. One approach to extract typical examples from this database is presented in this paper. An Autoassociative Neural Network is trained on all 3000 coded messages and then used to construct t...

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In a recent short paper and a report (see [Neto et al. 98] and [Neto and Costa 99]) it was shown that programming languages can be translated efficiently on recurrent (analog, rational weighted) neural nets, using bounded resources. This fact was achieved by creating a neural programming language called NETDEF, such that each program corresponds to a modular neural net that computes it. This fr...