← Efficient Pretraining Model based on Multi-Scale Local Visual Field Feature Reconstruction for PCB CT Image Element Segmentation FER-YOLO-Mamba: Facial Expression Detection and Classification Based on Selective State Space → # How Quality Affects Deep Neural Networks in Fine-Grained Image Classification この論文では、詳細な分類システムのパフォーマンスを向上させるために、非参照画像品質評価 (NRIQA) に基づくカットオフ ポイント選択 (CPS
Coding Train is a Youtube channel by Daniel Shiffman that covers anything from the basics of programming languages like JavaScript (with p5.js) and Java (with Processing) to generative algorithms like physics simulation, computer vision, and data visualization. In particular, these latter topics, which Shiffman bundles under the label "the Nature of Code", draw me to the…
[ next ] [ prev ] [ prev-tail ] [ tail ] [ up ] Chapter 17 Retraining neural networks by meditation The preceding chapter presented several directions in which information-processing should be changed to reduce suffering. We also saw some practical suggestions for reprogramming, such as seeing the uncertainty and uncontrollability of the world and reducing desires and self-needs. This will eventually lead to a reduction in reward loss, frustration, and suffering. Yet, the account of the preceding chapter ma
> TLDR: This post accompanies The Developmental Landscape of In-Context Learning by Jesse Hoogland, George Wang, Matthew Farrugia-Roberts, Liam Carro…
Defining Physics-Informed Neural Networks for Damage Detection Physics-informed neural networks (PINNs) represent a shift in how engineers approach
ISCA Archive Interspeech 2025 ISCA Archive Interspeech 2025 Efficient Streaming Speech Quality Prediction with Spiking Neural Networks Mattias Nilsson, Riccardo Miccini, Julian Rossbroich, Clément Laroche, Tobias Piechowiak, Friedemann Zenke As speech processing systems become more ubiquitous, the need for real-time, efficient speech quality prediction (SQP) is growing. Conventional artificial neural networks (ANNs) offer strong prediction performance but can be computationally demanding, which limits
Ian Goodfellow's Deep Learning PDF guide is essential reading for anyone interested in neural networks and deep learning. In this guide, Goodfellow provides a
For the last few months I’ve been slowly getting my head around the concepts of machine learning, artificial intelligence and neural networks. The impact tha
NeurIPS Proceedings Search Universality and individuality in neural dynamics across large populations of recurrent networks Niru Maheswaranathan, Alex Williams, Matthew Golub, Surya Ganguli, David Sussillo Advances in Neural Information Processing Systems 32 (NeurIPS 2019) Abstract Many recent studies have employed task-based modeling with recurrent neural networks (RNNs) to infer the computational function of different brain regions. These models are often assessed by quantitatively comparing the low-dimen
NeurIPS Proceedings Search Universality and individuality in neural dynamics across large populations of recurrent networks Niru Maheswaranathan, Alex Williams, Matthew Golub, Surya Ganguli, David Sussillo Advances in Neural Information Processing Systems 32 (NeurIPS 2019) Abstract Many recent studies have employed task-based modeling with recurrent neural networks (RNNs) to infer the computational function of different brain regions. These models are often assessed by quantitatively comparing the low-dimen