Ovaries play a pivotal role in production by generating eggs through oogenesis the female reproductive system. This is one crucial aspect of reproduction as are fertilized sperm which eventually leads to fertilization and ending embryo formation. often susceptible diseases like infertility, polycystic ovarian syndrome (PCOS), cancer etc. Screening follicles via ultrasound images can be great he...

We introduce the RAN 2 SOM (Reconngurable Architecure Neural Networks with Serially Operating Multipliers) architecture, a neural net architecture with a reconngurable interconnection scheme based on bit stream arithmetic. RAN 2 SOM nets are implemented using eld programmable gate array logic. By conducting the training phase in software and executing the actual application in hardware, connict...

In this article a new neural network architecture suitable for learning and generalization is discussed and developed. The architecture is inspired and modeled after quantum electronic devices and circuits where coherent electronic wavefunctions traveling through different parts of the circuit are combined together and result in interferences at detection nodes. These wavefunctions, represented...

The application of Deep Neural Networks for ranking in search engines may obviate the need for the extensive feature engineering common to current learning-to-rank methods. However, we show that combining simple relevance matching features like BM25 with existing Deep Neural Net models often substantially improves the accuracy of these models, indicating that they do not capture essential local...

Although recurrent neural nets have been moderately successful in learning to emulate finite-state machines (FSMs), the continuous internal state dynamics of a neural net are not well matched to the discrete behavior of an FSM. We describe an architecture, called DOLCE, that allows discrete states to evolve in a net as learning progresses. DOLCE consists of a standard recurrent neural net train...

This paper presents an approach of large neural net emulation by using new neuroprocessor NM6403, designed by RC Module. Model of neural net, hardware supported by neuroprocessor architecture, is discussed and some key features of NM6403, such us processing of data with variable bit length and two 64-bit external buses, are highlighted. Examples of emulation of neural nets by one neuroprocessor...