21 Result(s)
within
**angbo Shu
Computer Science
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Article
Dilation-erosion for single-frame supervised temporal action localization
To balance the annotation labor and the granularity of supervision, single-frame annotation has been introduced in temporal action localization. It provides a rough temporal location for an action but implicit...
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Article
Supervised Learning Strategy for Spiking Neurons Based on Their Segmental Running Characteristics
Supervised learning of spiking neurons is an effective simulation method to explore the learning mechanism of real neurons. Desired output spike trains are often used as supervised signals to control the synap...
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Article
A simple yet effective image stitching with computational suture zone
Image stitching is the process of combining two or more photographic images with spatially overlap** areas into a wider-view panorama accommodating the full-scale information. It suffers from ghosting or obv...
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Article
BCMask: a finer leaf instance segmentation with bilayer convolution mask
Whether in natural scenes or laboratory environments, leaf instance segmentation is still a challenging task in high-throughput plant phenotypic research. Because compared with normal instance objects, leaves ...
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Article
Wavelet-Attention CNN for image classification
The feature learning methods based on convolutional neural network (CNN) have successfully produced tremendous achievements in image classification tasks. However, the inherent noise and some other factors may...
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Article
Skip-attention encoder–decoder framework for human motion prediction
Human motion prediction aims to automatically predict the future motion sequence based on an observed human motion sequence. In this paper, we propose a novel skip-attention encoder–decoder (SAED) framework to...
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Chapter and Conference Paper
Spatiotemporal Perturbation Based Dynamic Consistency for Semi-supervised Temporal Action Detection
Temporal action detection usually relies on huge tagging costs to achieve significant performance. Semi-supervised learning, where only a small amount of data are annotated in the training set, can help reduce...
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Chapter and Conference Paper
Cross Fusion for Egocentric Interactive Action Recognition
The characteristics of egocentric interactive videos, which include heavy ego-motion, frequent viewpoint changes and multiple types of activities, hinder the action recognition methods of third-person vision f...
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Chapter and Conference Paper
A Novel CNN Architecture for Real-Time Point Cloud Recognition in Road Environment
To ameliorate the problems of disorder, sparseness, and floating occur for 3D LiDAR point cloud in the road environment, we propose a novel deep CNN architecture for real-time point cloud features extraction. ...
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Chapter and Conference Paper
Social Adaptive Module for Weakly-Supervised Group Activity Recognition
This paper presents a new task named weakly-supervised group activity recognition (GAR) which differs from conventional GAR tasks in that only video-level labels are available, yet the important persons within...
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Article
Image annotation refinement via 2P-KNN based group sparse reconstruction
Image annotation aims at predicting labels that can accurately describe the semantic information of images. In the past few years, many methods have been proposed to solve the image annotation problem. However...
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Chapter and Conference Paper
Temporal Action Localization Based on Temporal Evolution Model and Multiple Instance Learning
Temporal action localization in untrimmed long videos is an important yet challenging problem. The temporal ambiguity and the intra-class variations of temporal structure of actions make existing methods far f...
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Article
A content-based recommendation algorithm for learning resources
Automatic multimedia learning resources recommendation has become an increasingly relevant problem: it allows students to discover new learning resources that match their tastes, and enables the e-learning sys...
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Article
A Feature Selection Method for Projection Twin Support Vector Machine
In this paper, we propose a novel feature selection method which can suppress the input features during the process of model construction automatically. The main idea is to obtain better performance and sparse...
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Chapter and Conference Paper
Image Retrieval Based on Optimized Visual Dictionary and Adaptive Soft Assignment
In this work, we propose a new image retrieval scheme by identifying better visual representations and fusing multiple similarities based on multiple features. For visual representation, we propose a new coars...
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Chapter and Conference Paper
Global and Local C3D Ensemble System for First Person Interactive Action Recognition
Action recognition in first person videos is different from that in third person videos. In this paper, we aim to recognize interactive actions in first person videos. First person interactive actions contain ...
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Chapter and Conference Paper
Mini Neural Networks for Effective and Efficient Mobile Album Organization
In this paper, we present an auto mobile album organization system, which can automatically classify daily photos in mobile devices into six daily categories, e.g., Baby, Food, Party, Scenery, Selfie, and Sport. ...
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Chapter and Conference Paper
Recovering Overlap** Partials for Monaural Perfect Harmonic Musical Sound Separation Using Modified Common Amplitude Modulation
Monaural musical sound separation attempts to isolate one or more instrument sources from a mono-channel polyphonic mixture. The primary challenge is to accurately separate pitched musical sounds where their p...
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Article
KDE based outlier detection on distributed data streams in multimedia network
Multimedia networks hold the promise of facilitating large-scale, real-time data processing in complex environments. Their foreseeable applications will help protect and monitor military, environmental, safety...
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Chapter and Conference Paper
Computational Face Reader
The long-history Chinese anthroposcopy has demonstrated the often satisfying capabilities to tell the characteristics (mostly exaggerated as fortune) of a person by reading his/her face, i.e. understanding the...
