Reinforcement learning algorithms: A brief survey
Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …
A comprehensive survey and mathematical insights towards video summarization
P Narwal, N Duhan, KK Bhatia - Journal of Visual Communication and …, 2022 - Elsevier
Video Summarization is a technique to reduce the original raw video into a short video
summary. Video summarization automates the task of acquiring key frames/segments from …
summary. Video summarization automates the task of acquiring key frames/segments from …
Video summarization using deep learning techniques: a detailed analysis and investigation
One of the critical multimedia analysis problems in today's digital world is video
summarization (VS). Many VS methods have been suggested based on deep learning …
summarization (VS). Many VS methods have been suggested based on deep learning …
Mh-detr: Video moment and highlight detection with cross-modal transformer
Y Xu, Y Sun, B Zhai, Y Jia, S Du - 2024 International Joint …, 2024 - ieeexplore.ieee.org
With the increasing demand for video understanding, video moment and highlight detection
(MHD) has emerged as a critical research topic. MHD aims to localize all moments and …
(MHD) has emerged as a critical research topic. MHD aims to localize all moments and …
Video summarization with a convolutional attentive adversarial network
With the explosive growth of video data, video summarization, which attempts to seek the
minimum subset of frames while still conveying the main story, has become one of the …
minimum subset of frames while still conveying the main story, has become one of the …
Attention-guided multi-granularity fusion model for video summarization
Y Zhang, Y Liu, C Wu - Expert Systems with Applications, 2024 - Elsevier
Video summarization has attracted extensive attention benefiting from its valuable capability
to facilitate video browsing. While achieving notable improvement, existing methods still fail …
to facilitate video browsing. While achieving notable improvement, existing methods still fail …
Context recovery and knowledge retrieval: A novel two-stream framework for video anomaly detection
Video anomaly detection aims to find the events in a video that do not conform to the
expected behavior. The prevalent methods mainly detect anomalies by snippet …
expected behavior. The prevalent methods mainly detect anomalies by snippet …
A series-based deep learning approach to lung nodule image classification
Simple Summary Medical image classification is an important task in computer-aided
diagnosis, medical image acquisition, and mining. Although deep learning has been shown …
diagnosis, medical image acquisition, and mining. Although deep learning has been shown …
VSS-Net: visual semantic self-mining network for video summarization
Y Zhang, Y Liu, W Kang, R Tao - IEEE Transactions on Circuits …, 2023 - ieeexplore.ieee.org
Video summarization, with the target to detect valuable segments given untrimmed videos, is
a meaningful yet understudied topic. Previous methods primarily consider inter-frame and …
a meaningful yet understudied topic. Previous methods primarily consider inter-frame and …
Topic-aware video summarization using multimodal transformer
Y Zhu, W Zhao, R Hua, X Wu - Pattern Recognition, 2023 - Elsevier
Video summarization aims to generate a short and compact summary to represent the
original video. Existing methods mainly focus on how to extract a general objective synopsis …
original video. Existing methods mainly focus on how to extract a general objective synopsis …