Results 41 to 50 of about 418,765 (278)
Compression and Decompression of Audio Files Using the Arithmetic Coding Method
Scientific Journal of Informatics, 2019 Audio file size is relatively larger when compared to files with text format. Large files can cause various obstacles in the form of large space requirements for storage and a long enough time in the shipping process.
Parasian D. P Silitonga +1 more
doaj +1 more source
The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
Advanced Robotics Research, EarlyView.Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley +1 more source
Exclusively visual analysis of classroom group interactions
Physical Review Physics Education Research, 2016 Large-scale audiovisual data that measure group learning are time consuming to collect and analyze. As an initial step towards scaling qualitative classroom observation, we qualitatively coded classroom video using an established coding scheme with and ...
Laura Tucker +3 more
doaj +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Multiscale approaches to music audio feature learning [PDF]
, 2013 Content-based music information retrieval tasks are typically solved with a two-stage approach: features are extracted from music audio signals, and are then used as input to a regressor or classifier.
Dieleman, Sander, Schrauwen, Benjamin
core
High Quality Audio Coding with Mdctnet
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023 We propose a neural audio generative model, MDCTNet, operating in the perceptually weighted domain of an adaptive modified discrete cosine transform (MDCT). The architecture of the model captures correlations in both time and frequency directions with recurrent layers (RNNs).
Davidson, Grant +5 more
openaire +2 more sources
Advanced Science, EarlyView.We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich +2 more
wiley +1 more source
A simple lossy audio coding scheme based on the DWT [PDF]
, 2007 This paper proposes a simple scheme for audio coding that does not use perceptual models. The audio coder is based on the discrete wavelet transform to decorrelate signals, computed through the lifting scheme, and followed by Huffman coding.
Khevariya, Prashant K. +2 more
core
Signal, Image and Video Processing, 2013 In this paper, a new audio coding scheme combining the Hilbert transform and the empirical mode decomposition (EMD) is introduced. Based on the EMD, the coding is fully a data-driven approach. Audio signal is first decomposed adaptively, by EMD, into intrinsic oscillatory components called intrinsic mode functions (IMFs).
Khaldi, Kais +3 more
openaire +3 more sources
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Advanced Science, EarlyView.Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source