摘要:
An apparatus may include an image sensor that contains a multiplicity of pixel elements to detect one or more images and a processor circuit coupled to the image sensor. The apparatus may include a white balance module for execution on the processor circuit to receive, based upon a detected image of the one or more images, for a plurality of pixel elements of the multiplicity of pixel elements, three of more gray level values for a respective three or more color channels, to determine grayness likelihood functions for the respective three or more color channels, the three or more grayness likelihood functions comprising a proportional contribution to grey pixels of the detected image from one or more gray levels for each respective color channel, and to determine a white balance gain for two or more color channels based upon the determined grayness likelihood functions. Other embodiments are described and claimed.
摘要:
An apparatus may include an emitter to project a low resolution optical pattern and a high resolution optical pattern having a finer resolution than the low resolution optical pattern and a sensor to detect a composite image, where the composite image comprises a low resolution optical reflection pattern comprising reflection of the projected low resolution optical pattern and a high resolution optical reflection pattern comprising a reflection of the projected high resolution optical pattern. The apparatus may also include logic to determine object depth in a first depth range and object depth in a second depth range based upon the detected composite image. Other embodiments are disclosed and claimed.
摘要:
Embodiments herein relate to generating a personalized model using a machine learning process, identifying a learning engagement state of a learner based at least in part on the personalized model, and tailoring computerized provision of an educational program to the learner based on the learning engagement state. An apparatus to provide a computer-aided educational program may include one or more processors operating modules that may receive indications of interactions of a learner and indications of physical responses of the learner, generate a personalized model using a machine learning process based at least in part on the interactions of the learner and the indications of physical responses of the learner during a calibration time period, and identify a current learning state of the learner based at least in part on the personalized model during a usage time period. Other embodiments may be described and/or claimed.
摘要:
A mechanism is described for facilitating affect-based adaptive representation of user behavior relating to user expressions on computing devices according to one embodiment. A method of embodiments, as described herein, includes receiving a plurality of expressions communicated by a user. The plurality of expressions may include one or more visual expressions or one or more audio expressions. The method may further include extracting a plurality of features associated with the plurality of expressions, where each feature reveals a behavior trait of the user when the user communicates a corresponding expression. The method may further include mapping the plurality of expressions on a model based on the plurality of features, and discovering a behavioral reasoning associated with each of the plurality of expressions communicated by the user based on a mapping pattern as inferred from the model.