Disclosed is an image analysis method including inputting analysis data, including information regarding an analysis target cell to a deep learning algorithm having a neural network structure, and analyzing an image by calculating, by use of the deep learning algorithm, a probability that the analysis target cell belongs to each of morphology classifications of a plurality of cells belonging to a predetermined cell group.

Methods and systems for improving the interactivity of media content. The methods and systems are particularly applicable to the e-learning space, which features unique problems in engaging with users, maintaining that engagement, and allowing users to alter media assets to their specific needs. To address these issues, as well as improving interactivity of media assets generally, the methods and systems described herein provide for annotation and truncation of media assets. More particularly, the methods and systems described herein provide features such as annotation guidance and video condensation.

The present disclosure is to provide a computer-aided cell segmentation method for determining cellular Nuclear-to-Cytoplasmic ratio, which comprises acts of obtaining a cytological image using non-invasive in vivo biopsy technique; performing a nuclei segmentation process to identify a position and a contour of each of identified nuclei in the cytological image; performing a cytoplasmic process with an improved active contour model to obtain a cytoplasmic region for each identified nucleus based; and determine a cellular Nuclear-to-Cytoplasmic ratio based on the obtained nucleus and cytoplasmic regions.

The present disclosure is to provide a computer-aided cell segmentation method for determining cellular Nuclear-to-Cytoplasmic ratio, which comprises acts of obtaining a cytological image using non-invasive in vivo biopsy technique; performing a nuclei segmentation process to identify a position and a contour of each of identified nuclei in the cytological image; performing a cytoplasmic process with an improved active contour model to obtain a cytoplasmic region for each identified nucleus based; and determine a cellular Nuclear-to-Cytoplasmic ratio based on the obtained nucleus and cytoplasmic regions.

A method, apparatus, device, and storage medium for transforming a hairstyle are provided. The method may include: determining a face bounding box according to information on face key points of acquired face image; constructing grids according to the face bounding box; deforming, by using an acquired target hairstyle function, edge lines of at least a part of the constructed grids, which comprises the hairstyle, to obtain a deformed grid curve; determining a deformed hairstyle in the face image according to the deformed grid curve.

Technologies for thermal enhanced semantic segmentation include a computing device having a visible light camera and an infrared camera. The computing device receives a visible light image of a scene from the visible light camera and an infrared image of the scene from the infrared camera. The computing device registers the infrared image to the visible light image to generate a registered image. Registering the infrared image may include increasing resolution of the infrared image. The computing device generates a thermal boundary saliency image based on the registered infrared image. The computing device may generate the thermal boundary saliency image by applying a Gabor jet convolution to the registered infrared image. The computing device performs semantic segmentation on the visible light image, the registered infrared image, and the thermal boundary saliency image to generate a pixelwise semantic classification of the scene. Other embodiments are described and claimed.

Disclosed are systems and methods for improving interactions with and between computers in computerized security and content monitoring, hosting and providing devices, systems and/or platforms. The disclosed systems and methods provide a novel framework that adaptively distinguishes between known people versus unknown people based on a dynamically applied, anonymous facial recognition methodology. The disclosed framework provides such functionality by recognizing faces within captured images without storing any information or annotations regarding or revealing the captured person's identity. The framework is configured to adaptively learn to distinguish between faces seen for the first time and faces it has previously seen by locally processing a captured image and only sending face embeddings to a network location for future comparisons of subsequently, anonymously captured images.

A computer-implemented method for processing 3D image data of a dento-maxillofacial structure is described wherein the method may comprise the steps of: receiving 3D image data defining a volume of voxels, a voxel being associated with a radiodensity value and a position in the volume and the voxels providing a 3D representation of a dento-maxillofacial structure; using the voxels of the 3D image data to determine one or more 3D positional features for input to a first deep neural network, a 3D positional feature defining information aggregated from the entire received 3D data set; and, the first deep neural network receiving the 3D image data and the one or more positional features at its input and using the one or more 3D positional features to classify at least part of the voxels of the 3D image data into jaw, teeth and/or nerve voxels.

A method of classifying a near sun sky image includes at least one of the following steps: providing a recurrent neural network in the shape of a long short-term memory cell, the memory cell having at least an input gate, a neuron with a self-recurrent connection, a forget gate, and an output gate, and using a convolutional neural network, which includes, in the cited order, at least an input layer, one or more convolutional layers, an average pooling layer, and an output layer.

An apparatus for responding to vehicle water splashing includes a processor determining the vehicle water splashing based on image data of a nearby vehicle and determining dangerousness caused by the vehicle water splashing to perform vehicle control and storage storing information determined by the processor and the image data of the nearby vehicle.