Home /
Research
Showing 481 - 486 / 897
SamWalker++: recommendation with informative sampling strategy
CanWang, JiaweiChen, ShengZhou....
Published date-11/16/2020
RecommendationSystems
Recommendation from implicit feedback is a highly challenging task due to the lack of reliable negative feedback data. Existing methods address this challenge by treating all the un-observed data as …
Stylized Neural Painting
ZhengxiaZou, TianyangShi, ShuangQiu....
Published date-11/16/2020
Image-to-ImageTranslation, StyleTransfer
This paper proposes an image-to-painting translation method that generates vivid and realistic painting artworks with controllable styles. Different from previous image-to-image translation methods that formulate the translation as pixel-wise prediction, …
A New Dataset and Proposed Convolutional Neural Network Architecture for Classification of American Sign Language Digits
ArdaMavi....
Published date-11/16/2020
In our interviews with people who work with speech impaired persons, we learned that speech impaired people have difficulties in communicating with other people around them who do not know …
Deep learning in magnetic resonance prostate segmentation: A review and a new perspective
DavidGillespie, ConnahKendrick, IanBoon....
Published date-11/16/2020
Prostate radiotherapy is a well established curative oncology modality, which in future will use Magnetic Resonance Imaging (MRI)-based radiotherapy for daily adaptive radiotherapy target definition. However the time needed to …
iPerceive: Applying Common-Sense Reasoning to Multi-Modal Dense Video Captioning and Video Question Answering
AmanChadha, GurneetArora, NavpreetKaloty....
Published date-11/16/2020
CommonSenseReasoning, DenseVideoCaptioning, MachineTranslation, QuestionAnswering, VideoCaptioning, VideoQuestionAnswering
Most prior art in visual understanding relies solely on analyzing the "what" (e.g., event recognition) and "where" (e.g., event localization), which in some cases, fails to describe correct contextual relationships …
Cluster-Specific Predictions with Multi-Task Gaussian Processes
ArthurLeroy, PierreLatouche, BenjaminGuedj....
Published date-11/16/2020
Clustering, GaussianProcesses, Multi-TaskLearning
A model involving Gaussian processes (GPs) is introduced to simultaneously handle multi-task learning, clustering, and prediction for multiple functional data. This procedure acts as a model-based clustering method for functional …