Sentence examples for recognition speed from inspiring English sources
Recognition speed, correct response, and preference ranking were dependent variables in both experiments.
Many people's purchase decisions will come down to more basic questions: whether the phone looks nice, how good its camera is and whether their favourite apps are available for it, rather than its speech recognition speed and accuracy.
In one study, apparent dose-dependent effects on response, vigilance, and recognition speed were observed (1000 mg and 1500 mg/day).
Subsequently, the efficient RWN is applied to classify these fused features to further improve the recognition rate and the recognition speed.
ILBP overcomes the noise problems observed in the original LBP by searching over scale space, which is implemented using an integral image with a reduced number of features to achieve recognition speed.
To this end, we present a comprehensive review of the dominant building recognition systems by first grouping them into two categories: (i) effectiveness approaches that mainly focus on the improvement of recognition performance and (ii) efficiency methods that attempt to enhance the recognition speed.
"Companies like NVIDIA have launched products with more powerful GPUs at competitive prices, accelerating the image recognition speeds," Porco says.
The CRI is composed of six subtests measuring reaction time, visual recognition, and speed of information processing.
Performance was significantly worse in the morphine condition relative to one or both tramadol doses on measures of psychomotor speed/coordination (circular lights task), psychomotor speed/pattern recognition (DSST speed measure) and psychomotor speed/set shifting (trail-making tasks).
Altogether, results did not prove a benefit of the more naturalistic training setting regarding different training performances (recognition, performance speed, spatial orientation), self-perceived daily cognitive impairments, a real-life shopping task as well as various neuropsychological capabilities.
Recent advances in the field of visual neuroscience are increasingly being leveraged to develop biologically-plausible models and algorithms for visual cognition with the ultimate goal of improving object recognition accuracy, speed, and robustness.
