Google Inc.

Ping an Technology (shenzhen) Co., Ltd.

Vidient Systems, Inc

Nec Laboratories America, Inc.

Mei Han

Vivek Kwatra

Bo Gong

Yuchuan Gou

Michele Mae Covell

Yihong Gong

Saurabh Mathur

Jinghong Miao

Shumeet Baluja

Shengyang Dai

Ruei-Sung Lin

Hai Tao

Minghao Li

Jay Yagnik

Sergey Ioffe

Matthias Grundmann

Bo Wu

Peng Chang

Jui-Hsin Lai

Qixing Huang

Yi Zhao

Erik Murphy-Chutorian

Kyle Howard Heath

Ehud Rivlin

Wei Xu

Sangho Yoon

Juihsin Lai

Chen Du

Tian Xia

Nan Qiao

Charles Joseph Rosenberg

Shenghuo Zhu

Jingyu Cui

Hui Fang

Kun Li

Xi Yao

Ying Wu

Chuck Joseph Rosenberg

Jing-yu Cui

Qi Chen

Yanbo Zhang

Zhenjie Cao

Zhicheng Yang

Hao Zhang

Jing Xiao

Chaoping Qin

Hang Zhou

Xinyi Wu

Yiwei Wang

Qiancheng Wu

Bo Peng

Jui-hsin Lai

Hongchen Liu

According to one aspect of the present disclosure, a method of image enhancement is provided. The method may include receiving, by at least one processor, a query for an enhanced image of a queried region obtained by a remote sensor at a queried time. The method may include obtaining, by the at least one processor, an image dataset associated with the queried region from the remote sensor. In response to the image dataset including a plurality of image data associated with the queried region obtained by the remote sensor, the method may include generating, by the at least one processor, the enhanced image of the queried region using an intra-modal regression model.

System and method for multi-modal image enhancement based on time-adjacent image data

A system and method for unsupervised superpixel-driven instance segmentation of a remote sensing image are provided. The remote sensing image is divided into one or more image patches. The one or more image patches are processed to generate one or more superpixel aggregation patches based on a graph-based aggregation model, respectively. The graph-based aggregation model is configured to learn at least one of a spatial affinity or a feature affinity of a plurality of superpixels from each image patch and aggregate the plurality of superpixels based on the at least one of the spatial affinity or the feature affinity of the plurality of superpixels. The one or more superpixel aggregation patches are combined into an instance segmentation image.

System and method for unsupervised superpixel-driven instance segmentation of remote sensing image

A method and device for image generation are provided. The method includes: obtaining a text describing a content of an image to be generated; extracting, using a text encoder, a text feature vector from the text; determining a semantic mask as spatial constraints of the image to be generated; and automatically generating the image using a generative adversarial network (GAN) model according to the semantic mask and the text feature vector.

Method and device for text-based image generation

A system and a method for detecting animals in a region of interest are disclosed. An image that captures a scene in the region of interest is received. The image is fed to an animal detection model to produce a group of probability maps for a group of key points and a group of affinity field maps for a group of key point sets. One or more connection graphs are determined based on the group of probability maps and the group of affinity field maps. Each connection graph outlines a presence of an animal in the image. One or more animals present in the region of interest are detected based on the one or more connection graphs.

System and method for animal detection

A method for cutting or extracting video clips from a video, including the audio content relevant to points of particular interest, and combining the same for instruction or training on particular points; a computing device applying the method extracts text information from the spoken audio content of a video to be cut and obtains multiple paragraph segmentation positions as candidates for inclusion in a desired and finished presentation by analyzing the information from text representing the spoken audio content, the analysis being carried out by a semantic segmentation model. Candidate items of text are obtained by isolating pieces of text according to the paragraph segmentation positions. Time stamps of the candidate text segments are acquired, and candidate video clips are obtained by cutting the video according to the acquired time stamps.

Method for cutting video based on text of the video and computing device applying method

A system and a method for image-based crop identification are disclosed. The image-based crop identification system includes a database, a communication module and a model library. The database stores sample aerial data and annotated aerial data. The communication module is coupled to the database, and is configured to provide the sample aerial data to a user and receive the annotated aerial data from the user. The model library is coupled to the database, and is configured to obtain the annotated aerial data, train a crop classification model based on the annotated aerial data, and provide the trained crop classification model for subsequent crop identification. The annotated aerial data include determination of the type of the crop appearing in the sample aerial data.

System and method for image-based crop identification

A system and a method for super-resolution image processing in remote sensing are disclosed. One or more sets of multi-temporal images with an input resolution and one or more first target images with a first output resolution are generated from one or more data sources. The first output resolution is higher than the input resolution. Each set of multi-temporal images is processed to improve an image match in the corresponding set of multi-temporal images. The one or more sets of multi-temporal images are associated with the one or more first target images to generate a training dataset. A deep learning model is trained using the training dataset. The deep learning model is provided for subsequent super-resolution image processing.

System and method for super-resolution image processing in remote sensing

A method, applied to an apparatus for mammographic multi-view mass identification, includes receiving a main image, a first auxiliary image, and a second auxiliary image. The main image and the first auxiliary image are images of a breast of a person, and the second auxiliary image is an image of another breast of the person. The method further includes detecting the nipple location based on the main image and the first auxiliary image; generating a first probability map of the main image based on the main image, the first auxiliary image, and the nipple location; generating a second probability map of the main image based on the main image, the second auxiliary image, and the nipple location; and generating and outputting a fused probability map based on the first probability map and the second probability map.

Method and apparatus for mammographic multi-view mass identification

A device providing intelligent assistance in mobility for disabled people and others includes a mobility device and a lifting device detachably mounted on the mobility device. The lifting device includes a base frame, a retractable bracket structure, several wheels, a sitting pad, and a backrest. The wheels are mounted on a lower surface of the base frame and drive the lifting device to move. The retractable bracket structure is mounted on an upper surface of the base frame. The sitting pad is detachably mounted on the retractable bracket structure, and the backrest is rotatably mounted on the retractable bracket structure.

Intelligent mobility assistance device

A method for image generation and colorization includes displaying a drawing board interface; obtaining semantic labels of an image to be generated based on user input on the drawing board interface, each semantic label indicating a content of a region in the image to be generated; obtaining a color feature of the image to be generated; and automatically generating the image using a generative adversarial network (GAN) model according to the semantic labels and the color feature. The color feature is a latent vector input to the GAN model.

Method and device for image generation and colorization

An image generation method and a computing device employing the method includes: acquiring a plurality of original images; and processing the plurality of original images to obtain a training data set. An anti-neural network model is trained according to the training data set. A candidate image is generated through the trained anti-neural network model. The candidate image is complemented through a detail completion network model to obtain a target image according to a comparison image. Thereby, a style of the generated image is the same as that of the comparison image. A more realistic image can be randomly generated saving the time and energy of artificially creating an image.

Image generation method and computing device

In a crop identification method, multi-temporal sample remote sensing images labeled with first planting blocks of a specific crop are acquired. NDVI data of the sample remote sensing images are calculated. Noise of the NDVI data is reduced. A first multivariate Gaussian model is fitted based on de-noised NDVI data of the sample remote sensing image. Multi-temporal target remote sensing images are acquired. An NDVI time series of each pixel in the target remote sensing image is constructed. The NDVI time series is input to the first multivariate Gaussian model to obtain a likelihood value of each pixel displaying the specific crop in the remote sensing images. Second planting blocks of the specific crop in the target remote sensing images are determined accordingly. An accurate and robust identification result is thereby achieved.

Crop identification method and computing device

An environment monitoring method and an electronic device are provided, the method divides the satellite image into a plurality of first divided images with overlapping areas, a first multi-dimensional feature map is obtained by inputting the plurality of first divided images into an environment monitoring model, the environmental monitoring model fully combines the correlation between the environmental information of different dimensions, the environmental features of a plurality of different dimensions are correlated through an association network. By utilizing the environment monitoring method, a large area of the environment monitoring effectively is realized, and accuracy of environmental detection is improved.

Environment monitoring method and electronic device

A cultivated land recognition method in a satellite image includes: segmenting a satellite image of the Earth into a plurality of standard images; and recognizing cultivated land area in each of the standard images using a cultivated land recognition model to obtain a plurality of first images. Edges of ground level entities in each of the standard images are detected using an edge detection model to obtain a plurality of second images. Each of the first images and a corresponding one of the second images is merged to obtain a plurality of third images; and cultivated land images is obtained by segmenting each of the third images using a watershed segmentation algorithm. Not only can a result of recognizing cultivated land in satellite images of the Earth be improved, but an efficiency of recognizing the cultivated land also be improved. A computing device employing the method is also disclosed.

Cultivated land recognition method in satellite image and computing device

In a face swap method carried out by an electronic device, a first head image is segmented from a destination image. First facial landmarks and a first hair mask are obtained according to the first head image. A second head image is segmented from a source image. Second facial landmarks and a second hair mask are obtained according to the second head image. If at least one eye landmark in the second facial landmarks is covered by hair, the second head image and the second hair mask are processed and repaired so as to obtain a swapped-face image with eyes not covered by hair.

Face swap method and computing device

Growing community of inventors

Palo Alto, CA, United States of America

Mei Han