Contextual lstm (clstm) models for large scale nlp tasks
Documents exhibit sequential structure at multiple levels of abstraction (eg, sentences,
paragraphs, sections). These abstractions constitute a natural hierarchy for representing the …
paragraphs, sections). These abstractions constitute a natural hierarchy for representing the …
Mitigating test-time bias for fair image retrieval
We address the challenge of generating fair and unbiased image retrieval results given
neutral textual queries (with no explicit gender or race connotations), while maintaining the …
neutral textual queries (with no explicit gender or race connotations), while maintaining the …
Unsupervised deep feature learning for remote sensing image retrieval
Due to the specific characteristics and complicated contents of remote sensing (RS) images,
remote sensing image retrieval (RSIR) is always an open and tough research topic in the RS …
remote sensing image retrieval (RSIR) is always an open and tough research topic in the RS …
Aggregated deep local features for remote sensing image retrieval
Remote Sensing Image Retrieval remains a challenging topic due to the special nature of
Remote Sensing imagery. Such images contain various different semantic objects, which …
Remote Sensing imagery. Such images contain various different semantic objects, which …
Understanding and predicting cross-cultural food preferences with online recipe images
Predicting food preferences is challenging due to the numerous factors that can influence
individual taste. Cultural influences are one such factor that can significantly impact food …
individual taste. Cultural influences are one such factor that can significantly impact food …
Deep neural network approaches for detecting gastric polyps in endoscopic images
Gastrointestinal endoscopy is the primary method used for the diagnosis and treatment of
gastric polyps. The early detection and removal of polyps is vitally important in preventing …
gastric polyps. The early detection and removal of polyps is vitally important in preventing …
Utilizing a digital canvas to conduct a spatial-semantic search for digital visual media
The present disclosure includes methods and systems for searching for digital visual media
based on semantic and spatial information. In particular, one or more embodiments of the …
based on semantic and spatial information. In particular, one or more embodiments of the …
Learning of multimodal representations with random walks on the click graph
In multimedia information retrieval, most classic approaches tend to represent different
modalities of media in the same feature space. With the click data collected from the users' …
modalities of media in the same feature space. With the click data collected from the users' …
Localizing pedestrians in indoor environments using magnetic field data with term frequency paradigm and deep neural networks
Indoor environments are challenging for global navigation satellite systems and cripple its
performance. Magnetic field data-based positioning and localization has emerged as a …
performance. Magnetic field data-based positioning and localization has emerged as a …
Deep learning based decomposition for visual navigation in industrial platforms
In the heavy asset industry, such as oil & gas, offshore personnel need to locate various
equipment on the installation on a daily basis for inspection and maintenance purposes …
equipment on the installation on a daily basis for inspection and maintenance purposes …