The Likelihood Encoder for Lossy Source Compression [PDF]
, 2014 In this work, a likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on a soft-covering lemma.
Cuff, Paul +2 more
core +1 more source
LinkNet: Exploiting encoder representations for efficient semantic segmentation [PDF]
Visual Communications and Image Processing, 2017 Pixel-wise semantic segmentation for visual scene understanding not only needs to be accurate, but also efficient in order to find any use in real-time application.
Abhishek Chaurasia, E. Culurciello
semanticscholar +1 more source
Evaluating the Representational Hub of Language and Vision Models [PDF]
, 2019 The multimodal models used in the emerging field at the intersection of computational linguistics and computer vision implement the bottom-up processing of the `Hub and Spoke' architecture proposed in cognitive science to represent how the brain ...
Bernardi, Raffaella +3 more
core +2 more sources
Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network [PDF]
IEEE Transactions on Medical Imaging, 2017 Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterative ...
Hu Chen +7 more
semanticscholar +1 more source
Incorporating Hierarchy into Text Encoder: a Contrastive Learning Approach for Hierarchical Text Classification [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Hierarchical text classification is a challenging subtask of multi-label classification due to its complex label hierarchy. Existing methods encode text and label hierarchy separately and mix their representations for classification, where the hierarchy ...
Zihan Wang +4 more
semanticscholar +1 more source
DRE-SLAM: Dynamic RGB-D Encoder SLAM for a Differential-Drive Robot
Remote Sensing, 2019 The state-of-the-art visual simultaneous localization and mapping (V-SLAM) systems have high accuracy localization capabilities and impressive mapping effects.
Dongsheng Yang +6 more
doaj +1 more source
A Survey of the State-of-the-Art Models in Neural Abstractive Text Summarization
IEEE Access, 2021 Dealing with vast amounts of textual data requires the use of efficient systems. Automatic summarization systems are capable of addressing this issue.
Ayesha Ayub Syed +2 more
doaj +1 more source
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training [PDF]
AAAI Conference on Artificial Intelligence, 2019 We propose Unicoder-VL, a universal encoder that aims to learn joint representations of vision and language in a pre-training manner. Borrow ideas from cross-lingual pre-trained models, such as XLM (Lample and Conneau 2019) and Unicoder (Huang et al ...
Gen Li +4 more
semanticscholar +1 more source
RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 Despite pre-training’s progress in many important NLP tasks, it remains to explore effective pre-training strategies for dense retrieval. In this paper, we propose RetroMAE, a new retrieval oriented pre-training paradigm based on Masked Auto-Encoder (MAE)
Shitao Xiao +3 more
semanticscholar +1 more source
SimCommSys: taking the errors out of error-correcting code simulations
The Journal of Engineering, 2014 In this study, we present SimCommSys, a simulator of communication systems that we are releasing under an open source license. The core of the project is a set of C + + libraries defining communication system components and a distributed Monte Carlo ...
Johann A. Briffa, Stephan Wesemeyer
doaj +1 more source