Vision based bin picking is increasingly more di cult as the complexity of target objects increases We propose an e cient solution where complex objects are su ciently represented by simple features cues thus invariance to object complexity is established The re gion extraction algorithm utilized in our approach is capable of providing the focus of attention to the simple cues as a trigger towa...

We present preliminary work on automatically scoring constructed responses elicited as part of a certification test designed to measure the effectiveness of the test-taker as a K-12 music teacher. This content scoring differs from most previous work in that the responses are relatively long and are written by an adult population of generally proficient English writers. We obtain reasonably good...

We show that people’s travel destinations are predictable based on simple features of their home and destination. Using geotagged Twitter data from over 200,000 people in the U.S., with a median of 10 visits per user, we use machine learning to classify whether or not a person will visit a given location. We find that travel distance is the most important predictive feature. Ignoring distance, ...

Agreement is one of the most important as well studied linguistic features in field language processing. There are two views regarding processing Person and Number features. According to first view, defined distinct probes derivation, while latter view suggests that these bundle The current study investigated whether there any difference Turkish via ERP. findings indicated N400 + P600 pattern w...

Convolutional Neural Networks (CNNs) have been shown their performance in speech recognition systems for extracting features, and also acoustic modeling. In addition, CNNs have been used for robust speech recognition and competitive results have been reported. Convolutive Bottleneck Network (CBN) is a kind of CNNs which has a bottleneck layer among its fully connected layers. The bottleneck fea...

transfer learning allows the knowledge transference from the source (training dataset) to target (test dataset) domain. feature selection for transfer learning (f-mmd) is a simple and effective transfer learning method, which tackles the domain shift problem. f-mmd has good performance on small-sized datasets, but it suffers from two major issues: i) computational efficiency and predictive perf...

In this study, we investigated whether different morphosyntactic features, i.e. number and gender, play a role during the adult online comprehension of subject relative clauses (SRC) object (ORC), in Italian. This study was inspired by developmental studies showing that children struggle with ORC compared to SRC; yet, improves if head RC mismatch relevant features (e.g. but not gender Italian, ...