International Business Machines Corporation

Luciano De Andrade Barbosa

Matthias Kormaksson

Bianca Zadrozny

Cicero Nogueira Dos Santos

Marcelo Nery Dos Santos

Daria Bogdanova

An agricultural material application management system includes an automated agricultural data collection vehicle including a location sensor. The automated agricultural data collection vehicle includes a receiver that receives sensor data including crop information, a memory that stores the plurality of locations and the sensor data, and a processor that generates a mapping correlating the crop information with the plurality of locations in the agricultural area, and generates an agricultural material application recommendation for each of the plurality of locations based on the mapping. The agricultural material application management system includes an agricultural vehicle including an interface unit that interfaces with the automated agricultural data collection vehicle and receives the agricultural material application recommendations from the agricultural data collection vehicle. An agricultural material applicator applies an agricultural material to at least some of the plurality of locations, and a display provides the recommendations to a driver of the agricultural vehicle.

System and method for application of materials through coordination with automated data collection vehicles

Determining semantically equivalent text or questions using hybrid representations based on neural network learning. Weighted bag-of-words and convolutional neural networks (CNN) based distributed vector representations of questions or text may be generated to compute the semantic similarity between questions or text. Weighted bag-of-words and CNN based distributed vector representations may be jointly used to compute the semantic similarity. A pair-wise ranking loss function trains neural network. In one embodiment, the parameters of the system are trained by minimizing a pair-wise ranking loss function over a training set using stochastic gradient descent (SGD).

Machine learning and training a computer-implemented neural network to retrieve semantically equivalent questions using hybrid in-memory representations

Growing community of inventors

Rio de Janeiro, Brazil

Luciano De Andrade Barbosa