ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection
- Devamanyu Hazarika, Soujanya Poria, Rada Mihalcea, E. Cambria, Roger Zimmermann
- Computer Science, PsychologyConference on Empirical Methods in Natural…
- 2018
Interactive COnversational memory Network (ICON), a multi-modal emotion detection framework that extracts multimodal features from conversational videos and hierarchically models the self- and inter-speaker emotional influences into global memories to aid in predicting the emotional orientation of utterance-videos.
Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
- Devamanyu Hazarika, Soujanya Poria, Amir Zadeh, E. Cambria, Louis-Philippe Morency, Roger Zimmermann
- Computer ScienceNAACL-HLT
- 1 June 2018
A deep neural framework is proposed, termed conversational memory network, which leverages contextual information from the conversation history to recognize utterance-level emotions in dyadic conversational videos.
CASCADE: Contextual Sarcasm Detection in Online Discussion Forums
- Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, E. Cambria, Roger Zimmermann, Rada Mihalcea
- Computer ScienceInternational Conference on Computational…
- 1 May 2018
This paper proposes a ContextuAl SarCasm DEtector (CASCADE), which adopts a hybrid approach of both content- and context-driven modeling for sarcasm detection in online social media discussions.
Canopy transpiration and water fluxes in the xylem of the trunk of Larix and Picea trees — a comparison of xylem flow, porometer and cuvette measurements
- E. Schulze, J. Cermak, J. Kucera
- Environmental ScienceOecologia
- 1 July 1985
Investigation of the daily water balance of intact, naturally growing, adult Larix and Picea trees without major injury found that plant water status recovers with the decrease of transpiration and the refilling of the water storage sites.
A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP
- A. Bentaleb, Bayan Taani, A. Begen, C. Timmerer, Roger Zimmermann
- Computer ScienceIEEE Communications Surveys and Tutorials
- 2019
This survey provides an overview of the different methods proposed over the last several years of bitrate adaptation algorithms for HTTP adaptive streaming, leaving it to system builders to innovate and implement their own method.
SDNDASH: Improving QoE of HTTP Adaptive Streaming Using Software Defined Networking
- A. Bentaleb, A. Begen, Roger Zimmermann
- Computer ScienceACM Multimedia
- 1 October 2016
A new software defined networking (SDN) based dynamic resource allocation and management architecture for HAS systems is proposed, which aims to alleviate scalability issues and improve the per-client QoE.
SCADDAR: an efficient randomized technique to reorganize continuous media blocks
- Ashish Goel, C. Shahabi, S. Yao, Roger Zimmermann
- Computer ScienceProceedings / International Conference on Data…
- 7 August 2002
The SCADDAR approach is based on using a series of REMAP functions which can derive the location of a new block using only its original location as a basis and meets the objective to redistribute a minimum number of media blocks after disk scaling.
Viewable scene modeling for geospatial video search
- Sakire Arslan Ay, Roger Zimmermann, S. Kim
- Computer ScienceACM Multimedia
- 26 October 2008
An estimation model of the viewable area of a scene for indexing and searching and reports on a prototype implementation of a novel approach for querying videos based on the notion that the geographical location of the captured scene in addition to the location of a camera can provide valuable information and may be used as a search criterion in many applications.
Towards Natural and Accurate Future Motion Prediction of Humans and Animals
- Zhenguang Liu, Shuang Wu, Li Cheng
- Computer ScienceComputer Vision and Pattern Recognition
- 1 June 2019
A hierarchical recurrent network structure is developed to simultaneously encodes local contexts of individual frames and global contexts of the sequence, which achieves more natural and accurate predictions over state-of-the-art methods.
Key2Vec: Automatic Ranked Keyphrase Extraction from Scientific Articles using Phrase Embeddings
- Debanjan Mahata, John Kuriakose, R. Shah, Roger Zimmermann
- Computer ScienceNorth American Chapter of the Association for…
- 30 May 2018
An effective way of processing text documents for training multi-word phrase embeddings that are used for thematic representation of scientific articles and ranking of keyphrases extracted from them using theme-weighted PageRank is proposed.
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