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Article
Local Compressed Video Stream Learning for Generic Event Boundary Detection
Generic event boundary detection aims to localize the generic, taxonomy-free event boundaries that segment videos into chunks. Existing methods typically require video frames to be decoded before feeding into ...
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Chapter and Conference Paper
High-Fidelity Image Inpainting with GAN Inversion
Image inpainting seeks a semantically consistent way to recover the corrupted image in the light of its unmasked content. Previous approaches usually reuse the well-trained GAN as effective prior to generate r...
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Article
Context-guided feature enhancement network for automatic check-out
Powered by deep learning technology, automatic check-out (ACO) has made great breakthroughs. Nevertheless, because of the complex nature of real scenes, ACO is still an exceedingly testing task in the field of...
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Chapter and Conference Paper
Unbiased Multi-modality Guidance for Image Inpainting
Image inpainting is an ill-posed problem to recover missing or damaged image content based on incomplete images with masks. Previous works usually predict the auxiliary structures (e.g., edges, segmentation and c...
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Article
Non-deterministic and emotional chatting machine: learning emotional conversation generation using conditional variational autoencoders
Conversational responses are non-trivial for artificial conversational agents. Artificial responses should not only be meaningful and plausible, but should also (1) have an emotional context and (2) should be ...
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Chapter and Conference Paper
Spatial Attention Pyramid Network for Unsupervised Domain Adaptation
Unsupervised domain adaptation is critical in various computer vision tasks, such as object detection, instance segmentation, and semantic segmentation, which aims to alleviate performance degradation caused b...
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Chapter and Conference Paper
Evaluation for Two Bloom Filters’ Configuration
Bloom filter has been widely used in distributed systems. There are two typical types of Bloom filter construction methods. Past works have the notion that those two approaches have similar false positive rate...
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Chapter and Conference Paper
An Obstacle Detection Method Based on Binocular Stereovision
As the main tasks of Advance Driver Assistance Systems (ADAS), obstacle detection has attracted extensive attention. Traditional obstacle detection methods on the basis of monocular vision will lose its effect...
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Chapter and Conference Paper
Selection Optimization of Bloom Filter-Based Index Services in Ubiquitous Embedded Systems
In pervasive systems, data object is stored in distributed storage nodes. High performance indexing service plays an import rule in the efficient utilization of the data in ubiquitous computing. The embedded s...
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Chapter and Conference Paper
Learning Path Generation Method Based on Migration Between Concepts
The learning strategies often have a direct impact on learning effects. Often, the learning guidance is provided by teachers or experts. With the speed of knowledge renewal going faster and faster, it has been...
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Article
Training query filtering for semi-supervised learning to rank with pseudo labels
Semi-supervised learning is a machine learning paradigm that can be applied to create pseudo labels from unlabeled data for learning a ranking model, when there is only limited or no training examples availabl...
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Chapter
A Bloom Filter-Based Approach for Supporting the Representation and Membership Query of Multidimensional Dataset
Bloom filter has been utilized in set representation and membership query. However, the algorithm is not quite suitable for representing multidimensional dataset. The paper presents a novel data structure base...
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Chapter and Conference Paper
A Bloom Filter-Based Index for Distributed Storage Systems
The indexing technique, which is capable of locating an item, is a key component in distributed storage systems. There have been many solutions for the index in distributed systems. One of the problems is the ...
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Chapter and Conference Paper
Selecting Training Data for Learning-Based Twitter Search
Learning to rank is widely applied as an effective weighting scheme for Twitter search. As most learning to rank approaches are based on supervised learning, their effectiveness can be affected by the inclusio...
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Chapter and Conference Paper
An Adaptive Trust Prediction Framework for Diverse Data Model
The trust relationship is gaining importance in addressing information overload and personalized recommendation in rating based social networks. Current trust prediction models have significant drawbacks and l...
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Chapter and Conference Paper
An Intelligent Media Delivery Prototype System with Low Response Time
Streaming media has been increasing in the Internet as a popular form of content. However, the streaming media delivery between server and client browser still has problems to be solved, such as the poor proce...
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Chapter and Conference Paper
On Evaluating Query Performance Predictors
Query performance prediction (QPP) is to estimate the query difficulty without knowing the relevance assessment information. The quality of predictor is evaluated by the correlation coefficient between the pre...
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Chapter and Conference Paper
Evaluating Query Performance Predictors Based on Brownian Distance Correlation
Modern information retrieval system suffers from radical variance performance even though its mean performance is well. In order to solve this problem, the Query Performance Predictor, predicting the performan...
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Book
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Chapter
Conclusions
This book compares and contrasts three different approaches to deal with web information process. They are web sentiment analysis, collaborative filtering and trust-based collective view prediction.
