Sentence examples for most previous systems from inspiring English sources
Most previous systems for retrieving sound files using text queries, use a supervised multicategory learning approach where a classifier is trained for each semantic concept in the vocabulary.
Most previous systems are normalizing genes at mention-level and only local context surrounding a mention (e.g. the sentence where the mention was recognized) were employed.
Most previous analysis systems were based on costly observation apparatus at fixed sites, forecasting models were usually built on observations within a certain range, and some observations contained biases.
In contrast to the attention mechanisms used in most previous machine vision systems which drive attention based on the spatial location hypothesis, the mechanisms which direct visual attention in our system are object-driven as well as feature-driven.
In the past decades, most previous palmprint recognition systems that were designed on the basis of natural light, have achieved more preferable results in terms of recognition accuracy, matching speed, and security.
In Peru, most previous health information systems have required HC personnel to enter data for reporting purposes without receiving any feedback.
Furthermore, since no extra thermodynamic cycle or working fluid is demanded, the system architecture is more practical and simpler than most previous designs of system improvement.
Regarding to the ME task of DVS systems, most previous approaches attempt to reduce the computational cost by using fast ME algorithms, e.g., gray-coded bit-plane matching [9], two-bit transform [10], multiplication-free one-bit transform [11], Laplacian two-bit transform [12], and binary image matching of color weight [13].
Most previous work on this system focused on the effects of divergent host adaptation [ 46].
Most previous analyses of such dynamical systems are not exhaustive.
This study was unique in that most previous research on injury surveillance systems has focused on factors influencing data quality rather than on factors influencing the implementation of the system (McKinnon et al. [2009]).
