Etwas was ich ein paar Tagen gesehen habe und sehr interessant finde, ist dass man in in Shenzhen, China, seine iPhone-Speicherkapazität 800% verbessern kann. Vielleicht auch bis 1600% erhöhen. Mehr darüber können Sie hier anschauen:
Dr.-Ing. Sorin Liviu Jurj
Künstliche Intelligenz · Neuromorphe Systeme · Nachhaltigkeit
Top Beiträge
- Designing Neuromorphic 3D-Circuits using Memristors
- Ausgewählte Liste von Büchern aus meiner Bibliothek
- Spontane Ideen, die ich zwischen 2021 und 2023 hatte
- Spontane Ideen, die ich zwischen 2013 und 2020 hatte
- Powering and Evaluating Deep Learning-based Systems using Green Energy
- Sorin Liviu Jurj’s Ph.D. Defense – Stufe 2 (Doktortitel mit „Summa cum Laude“ erhalten)
- Sorin Liviu Jurj’s Ph.D. Defense – Stufe 1
- Ψ-Vortex: Structure-Regularized Recurrent Learning for Latent Thermal-Coupling Inference and Verilog-A Compact Modeling of 3-D Neuromorphic Devices
- Physics Structure-Informed Neural Networks in the TinyML Pipeline: Antisymmetry Preservation, Deployment Accounting, and Training-Budget Sensitivity
- From Cell-Specific Heuristics to Transferable Structural Search for Ramsey Graph Construction
- Modeling Glucocorticoid-Induced Renin Regulation from Sparse Data Using Physics-Informed Neural Networks
- Ψ-xLSTM: Automated Behavioral Verilog-A Generation from Distilled Physics-Informed xLSTM Networks for High-Frequency Device Modeling
- Ψ-HDL: Physics Structure-Informed Neural Networks for Hardware Description Language Generation
- A Physics-Regularized Neural Surrogate Framework for Printed Memristors
- PySpice-Simulated In Situ Learning with Memristor Emulation for Single-Layer Spiking Neural Networks
- Evaluating the Knowledge in Test Engineering Education using a Solar-powered Remote-controlled Flying Probe-Inspired In-Circuit Tester
- Efficient Implementation of Spiking Neural Networks for Inference using Ex-Situ Training
- SNNtrainer3D: Training Spiking Neural Networks using a User-friendly Application with 3D Architecture Visualization Capabilities
- Increasing the Solar Reliability Factor of a Dual-Axis Solar Tracker using an Improved Online Built-In Self-Test Architecture
- Improved Flying Probe-Inspired In-Circuit Tester for Practical Laboratory Activities
- Towards Safe and Sustainable Autonomous Vehicles Using Environmentally-Friendly Criticality Metrics
- Increasing the Safety of Adaptive Cruise Control using Physics-guided Reinforcement Learning
- Verification of Sigmoidal Artificial Neural Networks using iSAT
- Configurable Built-In Self-Test Architecture for Automated Testing of a Dual-Axis Solar Tracker
- Hybrid Testing of a Solar Tracking Equipment using In-Circuit Testing and JTAG Debugging Strategies
- Global Energy Production Computation of a Solar-Powered Smart Home Automation System using Reliability-Oriented Metrics
- Improving the Solar Reliability Factor of a Dual-Axis Solar Tracking System using Energy-Efficient Testing Solutions
- Fault Coverage-Aware Metrics for Evaluating the Reliability Factor of Solar Tracking Systems
- Environmentally-Friendly Metrics for Evaluating the Performance of Deep Learning Models and Systems
- Deep Learning-Based Computer Vision Application with Multiple Built-In Data Science-Oriented Capabilities
- Efficient Implementation of a Self-Sufficient Solar-Powered Real-Time Deep Learning-Based System
- Real-Time Identification of Animals found in Domestic Areas of Europe
- Mobile Application for Receipt Fraud Detection Based on Optical Character Recognition
- Identification of Traditional Motifs using Convolutional Neural Networks
- Affordable Flying Probe-Inspired In-Circuit-Tester for Printed Circuit Boards Evaluation with Application in Test Engineering Education
- Online Built-In Self-Test Architecture for Automated Testing of a Solar Tracking Equipment
- White-Box Testing Strategy for a Solar Tracking Device using NodeMcu Lua ESP8266 WiFi Network Development Board Module
- Position Optimization Method for a Solar Tracking Device using the Cast-Shadow Principle
- Technological solutions for throughput improvement of a Secure Hash Algorithm-256 engine
- Liste guter (und günstiger) internationaler Konferenzen für Doktoranden
- Wo kann ich Python lernen?
- Interessante Forschungsarbeiten
- Interessante Youtube-Kanäle zum Thema Geopolitik
My Profiles
Neueste Beiträge
Physics Structure-Informed Modeling for Emerging Electronics17. September 2026
Which Ψ Framework Should You Use? Ψ-NN, Ψ-HDL, Ψ-xLSTM, or Ψ-Vortex?11. September 2026
A from-scratch tutorial on Ψ-Vortex („Psi-Vortex“)11. September 2026
Ψ-Vortex: Structure-Regularized Recurrent Learning for Latent Thermal-Coupling Inference and Verilog-A Compact Modeling of 3-D Neuromorphic Devices10. September 2026- Today I Submitted My First MSCA-PF Research Proposal4. September 2026
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Schlagwörter
Artificial Intelligence China Computer Vision Deep Learning Deutschland Dual-axis solar tracker Fahrschule Butterfly Fahrschule Frankfurt Flavius Opritoiu Forschung Forschungsartikel FPGA Frankfurt Indien Indisches Essen Internet Künstliche Intelligenz LaTex Machine Learning Mircea Vladutiu Neu-Delhi neural network Neuromorphic Circuits Neuromorphic Computing Neuromorphic Engineering Neuronalen Netzwerken Nvidia Oldenburg physics-informed neural networks Pizza PostDoc printed memristors Promotionsstudent Promotionsstudium PSI-NN Python Raul Rotar Reinforcement Learning Reise Rumänien SIITME Solar energy Solar Tracker Urlaub Vegetarisches Essen
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