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Low-latency processing
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
ReSpec: Relevance and Specificity Grounded Online Filtering for Learning on Video-Text Data Streams
SuperEIO: Self-Supervised Event Feature Learning for Event Inertial Odometry
Event-Driven Implementation of a Physical Reservoir Computing Framework for superficial EMG-based Gesture Recognition
Learning LLM Preference over Intra-Dialogue Pairs: A Framework for Utterance-level Understandings
Wandering around: A bioinspired approach to visual attention through object motion sensitivity
Continuous signal sparse encoding using analog neuromorphic variability
Decoding finger velocity from cortical spike trains with recurrent spiking neural networks
EON-1: A Brain-Inspired Processor for Near-Sensor Extreme Edge Online Feature Extraction
Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation
Modified Parametric Multichannel Wiener Filter \\for Low-latency Enhancement of Speech Mixtures with Unknown Number of Speakers
OpenHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science
Machine Learning 5G Attack Detection in Programmable Logic
Streaming parallel transducer beam search with fast-slow cascaded encoders
High-Fidelity and Low-Latency Universal Neural Vocoder based on Multiband WaveRNN with Data-Driven Linear Prediction for Discrete Waveform Modeling
End-to-End Memristive HTM System for Pattern Recognition and Sequence Prediction
A Multi-Phase Gammatone Filterbank for Speech Separation via TasNet
S-ConvNet: A Shallow Convolutional Neural Network Architecture for Neuromuscular Activity Recognition Using Instantaneous High-Density Surface EMG Images
Feed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code
Optimising The Input Window Alignment in CD-DNN Based Phoneme Recognition for Low Latency Processing
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.