Abstract: The present invention is directed to a nitrogen containing surfactant composition comprising at least one nitrogen containing surfactant of structure (h) or structure (i). The nitrogen containing surfactant of structure (h) is as shown below: Structure (h). The nitrogen containing surfactant of structure (i) is as shown below: Structure (i). The present invention is also directed to an agricultural composition comprising at least one agrochemical and at least one nitrogen containing surfactant composition of the present invention.

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: An object detector includes a bottom-up object hypotheses generation unit; a top-down object search with supervised descent unit; and an object re-localization unit with a localization model.

Abstract: An object detector includes a bottom-up object hypotheses generation unit; a top-down object search with supervised descent unit; and an object re-localization unit with a localization model.

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: 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: Computerized methods and systems for the analysis of textual data, including: receiving, from one or more memories at one or more processors, textual data; using the processors, formatting the textual data for analysis and applying a probabilistic topic model to the textual data to extract semantically meaningful topics that collectively describe it; using a keyword weighting module, generating a topic cloud view representing the topics as a tagcloud with each being associated with a plurality of keywords; using a topic ordering module, generating a document distribution view representing a distribution of the textual data across multiple topics; using a document entropy calculation module, generating a document scatterplot view representing how many topics are attributable to the textual data; using a temporal topic trend calculation module, generating a temporal view representing changes in the occurrence of topics over time; and displaying one or more of the views to a user.

Abstract: Systems and methods are disclosed to respond to a query for one or more images by using a processor, applying an indexing strategy which processes images as grouplets rather than individual single images; generating a two layer indexing structure with a group layer, each associated with one or more images in an image layer; cross-indexing the images into two or more groups; and retrieving near duplicate images with the cross-indexed images and the grouplets.

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 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 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: 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.