CSI NN - Reverse Engineering of Neural Network Architectures Through Electromagnetic Side Channel
Reverse engineering neural networks through electromagnetic side channels, revealing architecture details like activation functions, layers, neurons, and weights using non-invasive techniques on ARM Cortex-M3 microcontrollers.
Understanding Neural Network Architectures with Attention and Diffusion
Explore Attention and Diffusion models in neural networks, focusing on their applications in language processing and image synthesis, with simplified diagrams for visual learners.
Honey Bee Conservation Using Deep Learning
Explore DeepBee: an innovative tool using deep learning for automatic honeybee colony assessment, streamlining the process of counting and classifying comb cells for beekeepers.
Deep Learning - The Final Frontier for Time Series Analysis
Explore deep learning's potential in time series analysis, covering classification, prediction, and anomaly detection. Learn how neural networks can revolutionize processing of sequential data across various domains.
Dive into Deep Learning with Scala
Explore deep learning fundamentals and implementation in Scala, covering neural networks, computer vision, and practical applications with hands-on examples and library comparisons.
AI Assisted Development
Exploring AI's impact on Scala development, from TDD to code generation, and discussing future possibilities for AI-assisted programming.
EfficientNet Paper Walkthrough
Comprehensive walkthrough of the EfficientNet paper, exploring model scaling, proposed methods, and results. Offers insights into innovative approaches for improving neural network efficiency.
SpineNet - Learning Scale-Permuted Backbone for Recognition and Localization
Explores SpineNet, a novel CNN architecture using scale-permuted features and cross-scale connections, outperforming traditional models in object detection and classification tasks.
PirateNets - Physics-Informed Deep Learning with Residual Adaptive Networks
Explore PirateNets: a novel deep learning architecture for solving PDE-governed problems, offering improved stability and efficiency over traditional physics-informed neural networks.
Introduction to Artificial Neural Networks - JSALT 2023
Explore artificial neural networks: fundamentals, architectures, and applications in this comprehensive introduction from JSALT 2023 workshop.
Capturing Computation with Algorithmic Alignment
Explore algorithmic alignment in neural networks, its implications for architecture design, and its potential for building future intelligent systems.