Résultats de la recherche - decoding (Algorithmssics OR (algorithm OR algorithm))

Evaluating Single Event Upsets in Deep Neural Networks for Semantic Segmentation: an embedded system perspective par Gutiérrez-Zaballa, Jon, Basterretxea, Koldo, Echanobe, Javier

Table des matières: “…As the deployment of artifical intelligence (AI) algorithms at edge devices becomes increasingly…”
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Efficient Approximate Degenerate Ordered Statistics Decoding for Quantum Codes via Reliable Subset Reduction par Kung, Ching-Feng, Kuo, Kao-Yueh, Lai, Ching-Yi

Table des matières: “…Efficient and scalable decoding of quantum codes is essential for high-performance quantum error…”
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Cepstrum-based interferometric microscopy (CIM) for quantitative phase imaging par Rubio-Oliver, Ricardo, Garcia, Javier, Zalevsky, Z., Picazo-Bueno, J., Mico, V.

Table des matières: “…A universal methodology for coding-decoding the complex amplitude field of an imaged sample…”
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A Genetic Algorithm-Based Approach for Automated Optimization of Kolmogorov-Arnold Networks in Classification Tasks par Long, Quan, Wang, Bin, Xue, Bing, Zhang, Mengjie

Table des matières: “… requiring manual intervention and parameter tuning. This paper proposes GA-KAN, a genetic algorithm-based…”
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InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU par Lee, Heejun, Park, Geon, Suh, Jaduk, Hwang, Sung Ju

Table des matières: “… token pruning algorithm. Our method also allows generalization to longer sequences by selectively…”
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DCentNet: Decentralized Multistage Biomedical Signal Classification using Early Exits par Li, Xiaolin, Huang, Binhua, Cardiff, Barry, John, Deepu

Table des matières: “… encoder-decoder pairs at EEPs, the system compresses large feature maps before transmission, significantly…”
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Fuzzy Speculative Decoding for a Tunable Accuracy-Runtime Tradeoff par Holsman, Maximilian, Huang, Yukun, Dhingra, Bhuwan

Table des matières: “… Speculative Decoding (FSD) - a decoding algorithm that generalizes SD by accepting candidate tokens based…”
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OCL: Ordinal Contrastive Learning for Imputating Features with Progressive Labels par Baek, Seunghun, Sim, Jaeyoon, Wu, Guorong, Kim, Won Hwa

Table des matières: “… decoder to reconstruct the original measures conditioned on their imaging modalities. The encoder includes…”
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Highly Efficient Direct Analytics on Semantic-aware Time Series Data Compression par Sun, Guoyou, Karras, Panagiotis, Zhang, Qi

Table des matières: “… for semantic encoding and decoding, they struggle with the sequential nature of time series data and high…”
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Magnitude-Phase Dual-Path Speech Enhancement Network based on Self-Supervised Embedding and Perceptual Contrast Stretch Boosting par Mattursun, Alimjan, Wang, Liejun, Yu, Yinfeng, Ma, Chunyang

Table des matières: “… starts by applying the perceptual contrast stretching (PCS) algorithm to enhance the magnitude-phase…”
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HarmonySeg: Tubular Structure Segmentation with Deep-Shallow Feature Fusion and Growth-Suppression Balanced Loss par Huang, Yi, Zhang, Ke, Liu, Wei, Wang, Yuanyuan, Patel, Vishal M., Lu, Le, Han, Xu, Jin, Dakai, Yan, Ke

Table des matières: “… exist in algorithm design when faced with diverse sizes, complex topologies, and (often) incomplete data…”
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Full-Diversity Construction-D Lattices: Design and Decoding Perspective on Block-Fading Channels par Sadeghi, Maryam, Khodaiemehr, Hassan, Feng, Chen

Table des matières: “… this, we develop an efficient decoding algorithm designed specifically for full-diversity Construction-D…”
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Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D par Arnaud, Sergio, McVay, Paul, Martin, Ada, Majumdar, Arjun, Jatavallabhula, Krishna Murthy, Thomas, Phillip, Partsey, Ruslan, Dugas, Daniel, Gejji, Abha, Sax, Alexander, Berges, Vincent-Pierre, Henaff, Mikael, Jain, Ayush, Cao, Ang, Prasad, Ishita, Kalakrishnan, Mrinal, Rabbat, Michael, Ballas, Nicolas, Assran, Mido, Maksymets, Oleksandr, Rajeswaran, Aravind, Meier, Franziska

Table des matières: “… and AR devices. Key to our approach is 3D-JEPA, a novel self-supervised learning (SSL) algorithm…”
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Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images par Qiu, Tian, Nichani, Arjun, Tadayontahmasebi, Rasta, Jeong, Haewon

Table des matières: “… in neural compression algorithms by analyzing nine popular models and their variants. Through…”
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Trellis Waveform Shaping for Sidelobe Reduction in Integrated Sensing and Communications: A Duality with PAPR Mitigation par Pu, Henglin, Li, Husheng, Han, Zhu, Poor, H. Vincent

Table des matières: “… the PAPR. In this paper, inspired by PAPR reduction algorithms in OFDM, we employ trellis shaping in OFDM…”
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Your Language Model Can Secretly Write Like Humans: Contrastive Paraphrase Attacks on LLM-Generated Text Detectors par Fang, Hao, Kong, Jiawei, Zhuang, Tianqu, Qiu, Yixiang, Gao, Kuofeng, Chen, Bin, Xia, Shu-Tao, Wang, Yaowei, Zhang, Min

Table des matières: “… reduces when faced with advanced detection algorithms. To address this, we propose \textbf{Co}ntrastive…”
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Toward Fully Neuromorphic Receivers for Ultra-Power Efficient Communications par Katsaros, George N., Nikitopoulos, Konstantinos

Table des matières: “… efforts mainly focused on mapping isolated communication algorithms onto spiking networks, often…”
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Multi-Spectral Gaussian Splatting with Neural Color Representation par Meyer, Lukas, Grün, Josef, Weiherer, Maximilian, Egger, Bernhard, Stamminger, Marc, Franke, Linus

Table des matières: “… red, without any algorithmic changes. Unlike existing 3DGS-based frameworks that treat each modality…”
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Onboard Mission Replanning for Adaptive Cooperative Multi-Robot Systems par Kwan, Elim, Qureshi, Rehman, Fletcher, Liam, Laganier, Colin, Nockles, Victoria, Walters, Richard

Table des matières: “… communication links to centralised compute. Fast, on-board replanning algorithms are therefore needed to enhance…”
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The complete weight distribution of a family of irreducible cyclic codes of dimension two par Vega, Gerardo, Hernández, Félix

Table des matières: “… of linear codes are also important due to their efficient encoding and decoding algorithms. Because…”
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