Optimum 发表于 2025-3-23 10:07:28
Head Detection of the Car Occupant Based on Contour Models and Support Vector Machines detecting the head. Our application domain is the telematics, especially within the car. In such environment, the illumination level is very variable. Moreover, we may need to use infrared illumination to capture the occupant in the night. Therefore, it is difficult to utilize the color information.lethargy 发表于 2025-3-23 15:34:36
http://reply.papertrans.cn/47/4671/467033/467033_12.pngRadiculopathy 发表于 2025-3-23 19:37:07
http://reply.papertrans.cn/47/4671/467033/467033_13.pngMedicaid 发表于 2025-3-24 02:03:37
Feature-Table-Based Automatic Question Generation for Tree-Based State Tying: A Practical Implementaately phonetic) questions have to be carefully defined. This may be extremely time consuming and require a considerable amount of resources. The system proposed in this paper provides a more elegant and efficient way to generate a set of questions from a simple feature table of the type employed in phonetic studies.奖牌 发表于 2025-3-24 05:55:42
Speeding Up Dynamic Search Methods in Speech Recognitionchniques can be applied together, and their combination could significantly speed up the recognition process. The run-times we obtained were 22 times faster than the basic dynamic search method, and 8 times faster than the multi-stack decoding method.讽刺 发表于 2025-3-24 08:14:58
http://reply.papertrans.cn/47/4671/467033/467033_16.png善变 发表于 2025-3-24 12:17:18
http://reply.papertrans.cn/47/4671/467033/467033_17.png流利圆滑 发表于 2025-3-24 18:53:20
Movement Prediction from Real-World Images Using a Liquid State Machinetwork. Connections to some output neurons are trained by linear regression to predict the position of a ball in various time steps ahead. Our results support the idea that learning with a liquid state machine can be applied not only to designed data but also to real, noisy data.periodontitis 发表于 2025-3-24 20:49:51
http://reply.papertrans.cn/47/4671/467033/467033_19.pngCapture 发表于 2025-3-25 00:37:15
Spoken Language Communication with Machines: The Long and Winding Road from Research to Businesstheoretical foundations in the 1980s, to the incremental improvement phase of the 1990s and 2000s. Then a perspective is given on the current conversational technology market and industry, with an analysis of its business value and commercial models.