Abstract: Systems and methods are disclosed for autonomous driving with only a single camera by moving object localization in 3D with a real-time framework that harnesses object detection and monocular structure from motion (SFM) through the ground plane estimation; tracking feature points on moving cars a real-time framework to and use the feature points for 3D orientation estimation; and correcting scale drift with ground plane estimation that combines cues from sparse features and dense stereo visual data.

Abstract: Systems and methods are disclosed for object detection by receiving an image and extracting features therefrom; applying a learning process to determine sub-regions and select predetermined pooling regions; and performing selective max-pooling to choose one or more feature regions without noises.

Abstract: Systems and methods are disclosed for detecting an object in an image by determining convolutional neural network responses on the image; mapping the responses back to their spatial locations in the image; and constructing features densely extract shift invariant activations of a convolutional neural network to produce dense features for the image.

Abstract: Systems and methods for object detection by receiving an image; segmenting the image and identifying candidate bounding boxes which may contain an object; for each candidate bounding box, dividing the box into overlapped small patches, and extracting dense features from the patches; during a training phase, applying a learning process to learn one or more discriminative classification models to classify negative boxes and positive boxes; and during an operational phase, for a new box generated from the image, applying the learned classification model to classify whether the box contains an object.

Abstract: Systems and methods are disclosed for object detection by receiving an image; segmenting the image; extracting features from the image; and performing a dimension-wise spatial layout selection to pick up dimensions inside a discriminative spatial region for classification.

Abstract: Foreground objects of interest are distinguished from a background model by dividing a region of interest of a video data image into a grid array of individual cells. Each of the cells are labeled as foreground if accumulated edge energy within the cell meets an edge energy threshold, or if color intensities for different colors within each cell differ by a color intensity differential threshold, or as a function of combinations of said determinations.

Abstract: Cervical cancer is one of the most common malignancies and is associated with a dismal prognosis. The most common therapeutic option for cervical cancer consists of surgery in early stages, and chemotherapy or radiotherapy in more advanced stages of the disease. Although treatment options have increased for some patients, overall progress has been modest. This invention relates to a method for treating cancer comprising administering an anti-cancer compound. More particularly, the present invention relates to an anti-cervical-cancer compound for treating human cervical cancer and tumor.

Abstract: Prostate cancer is the most commonly diagnosed cancer in males and one of the leading causes of cancer death. Although treatment options have increased for some patients, overall progress has been modest. Thus, there is a great need to develop new treatments. This invention relates to a method for treating cancer comprising using an anti-cancer compound. More particularly, it relates to an anti-prostate cancer compound that can be isolated from Garcinia esculenta or chemically synthesized and its specific anticancer/antitumor activity. The invention has a specific application in treating human prostate cancer.

Abstract: Foreground objects of interest are distinguished from a background model by dividing a region of interest of a video data image into a grid array of individual cells that are each smaller than that a foreground object of interest. More particularly, image data of the foreground object of interest spans a contiguous plurality of the cells. Each of the cells are labeled as foreground if accumulated edge energy within the cell meets an edge energy threshold, if color intensities for different colors within each cell differ by a color intensity differential threshold, or as a function of combinations of said determinations in view of one or more combination rules.

Abstract: A method for driving light adjustments, a device therefor and a light adjustable lamp including the device are disclosed. The device includes a light source driving circuit, an MCU and a temporary power supplying circuit. The MCU includes a current detecting module, an analyzing and processing module and a storage module. The analyzing and processing module obtains a connecting signal or a disconnecting signal of the light source driving circuit and thereafter extracts a stored firmware program of gradually varying brightness of a light source or stored information about a constant brightness state of the light source from the storage module for analyzing and processing, so as to generate a controlling signal of adjusting the brightness of the light source and send the controlling signal into the light source driving circuit. Then the light source driving circuit adjusts the brightness of the light source according to the controlling signal.

Abstract: Systems and methods are disclosed to search for a query image, by detecting local invariant features and local descriptors; retrieving best matching images by quantizing the local descriptors with a vocabulary tree; and reordering retrieved images with results from the vocabulary tree quantization.

Abstract: An image retrieval method includes learning multiple object category classifiers with a processor offline and generating classifications scores of images as the semantic attributes; performing vocabulary tree based image retrieval using local features with semantic-aware co-indexing to jointly embed two distinct cues offline for near-duplicate image retrieval; and identifying top similar or dissimilar images using multiple semantic attributes.

Abstract: Systems and methods are disclosed for object detection by receiving an image; segmenting the image; extracting features from the image; and performing a dimension-wise spatial layout selection to pick up dimensions inside a discriminative spatial region for classification.

Abstract: Systems and methods are disclosed for autonomous driving with only a single camera by moving object localization in 3D with a real-time framework that harnesses object detection and monocular structure from motion (SFM) through the ground plane estimation; tracking feature points on moving cars a real-time framework to and use the feature points for 3D orientation estimation; and correcting scale drift with ground plane estimation that combines cues from sparse features and dense stereo visual data.

Abstract: Systems and methods are disclosed for object detection by receiving an image and extracting features therefrom; applying a learning process to determine sub-regions and select predetermined pooling regions; and performing selective max-pooling to choose one or more feature regions without noises.

Abstract: Systems and methods for object detection by receiving an image; segmenting the image and identifying candidate bounding boxes which may contain an object; for each candidate bounding box, dividing the box into overlapped small patches, and extracting dense features from the patches; during a training phase, applying a learning process to learn one or more discriminative classification models to classify negative boxes and positive boxes; and during an operational phase, for a new box generated from the image, applying the learned classification model to classify whether the box contains an object.

Abstract: Systems and methods are disclosed to categorize images by detecting local features for each image; applying a tree structure to index local features in the images; and extracting a rank list of candidate images with category tags based on a tree indexing structure to estimate a label of a query image.

Abstract: Disclosed is a natural compound, Oblongifolin C, isolated from a natural plant comprising Garcinia species such as Garcinia yunnanesis Hu, for its effects of anti-migration and anti-invasion against cancer and its use as an anticancer drug. The treated cancers comprise cervical cancers and esophageal cancers. The cancer treatment comprises inhibition of cancer metastasis and inhibition of autophagic flux.

Abstract: An image retrieval method includes learning multiple object category classifiers with a processor offline and generating classifications scores of images as the semantic attributes; performing vocabulary tree based image retrieval using local features with semantic-aware co-indexing to jointly embed two distinct cues offline for near-duplicate image retrieval; and identifying top similar or dissimilar images using multiple semantic attributes.

Abstract: The present invention generally relates to a viscoelastic fluids, thickened acid compositions and the like and to methods of using said gelled compositions. The thickened compositions of the present invention can usefully be employed in methods of stimulating and/or modifying the permeability of underground formations, in drilling fluids, completion fluids, workover fluids, acidizing fluids, fracturing, gravel packing and the like.