Imagen de Portada

Investigating Target Class Influence on Neural Network Compressibility for Energy-Autonomous Avian Monitoring

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Brolich, Nina, Geis, Simon, Kasper, Maximilian, Barnhill, Alexander, Plinge, Axel, Seuß, Dominik
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

PrototypeNAS: Rapid Design of Deep Neural Networks for Microcontroller Units
por: Deutel, Mark, et al.
Publicado: (2026)

Pareto Optimal Benchmarking of AI Models on ARM Cortex Processors for Sustainable Embedded Systems
por: Jain, Pranay, et al.
Publicado: (2026)

C-MCTS: Safe Planning with Monte Carlo Tree Search
por: Parthasarathy, Dinesh, et al.
Publicado: (2023)

DH on the Edge?
por: Brolich, Nina
Publicado: (2026)

Two Steps Are All You Need: Efficient 3D Point Cloud Anomaly Detection with Consistency Models
por: A, Pranav, et al.
Publicado: (2026)

Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule
por: Periyasamy, Maniraman, et al.
Publicado: (2024)

Neural Class Expression Synthesis
por: Kouagou, N'Dah Jean, et al.
Publicado: (2021)

Collateral Damage Assessment Model for AI System Target Engagement in Military Operations
por: Maathuis, Clara, et al.
Publicado: (2025)

Directly Follows Graphs Go Predictive Process Monitoring With Graph Neural Networks
por: Lischka, Attila, et al.
Publicado: (2025)

Class-Aware Pruning for Efficient Neural Networks
por: Jiang, Mengnan, et al.
Publicado: (2023)

Trust or Bust: Ensuring Trustworthiness in Autonomous Weapon Systems
por: Cools, Kasper, et al.
Publicado: (2024)

Self-Compressing Neural Networks
por: Cséfalvay, Szabolcs, et al.
Publicado: (2023)

TSOM: Small Object Motion Detection Neural Network Inspired by Avian Visual Circuit
por: Hu, Pignge, et al.
Publicado: (2024)

Expected Attention: KV Cache Compression by Estimating Attention from Future Queries Distribution
por: Devoto, Alessio, et al.
Publicado: (2025)

The Power of Training: How Different Neural Network Setups Influence the Energy Demand
por: Geißler, Daniel, et al.
Publicado: (2024)

Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents
por: Backlund, Axel, et al.
Publicado: (2025)

Barlow Twins Deep Neural Network for Advanced 1D Drug-Target Interaction Prediction
por: Schuh, Maximilian G., et al.
Publicado: (2024)

On the Expressive Power of Graph Neural Networks
por: Nalwade, Ashwin, et al.
Publicado: (2024)

Compressing Deep Neural Networks Using Explainable AI
por: Soroush, Kimia, et al.
Publicado: (2025)

Utilizing Description Logics for Global Explanations of Heterogeneous Graph Neural Networks
por: Köhler, Dominik, et al.
Publicado: (2024)

Do Vision-Language-Models show human-like logical problem-solving capability in point and click puzzle games?
por: Triebel, Maximilian, et al.
Publicado: (2026)

Evaluation of Multilingual LLMs Personalized Text Generation Capabilities Targeting Groups and Social-Media Platforms
por: Macko, Dominik
Publicado: (2026)

Compressing Neural Networks Using Tensor Networks with Exponentially Fewer Variational Parameters
por: Qing, Yong, et al.
Publicado: (2023)

Tailoring Adversarial Attacks on Deep Neural Networks for Targeted Class Manipulation Using DeepFool Algorithm
por: Labib, S. M. Fazle Rabby, et al.
Publicado: (2023)

Monitor Placement for Fault Localization in Deep Neural Network Accelerators
por: Liu, Wei-Kai
Publicado: (2023)

Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
por: Schnaus, Dominik, et al.
Publicado: (2023)

Monte-Carlo Tree Search with Neural Network Guidance for Lane-Free Autonomous Driving
por: Peridis, Ioannis, et al.
Publicado: (2026)

Efficient Single-Step Framework for Incremental Class Learning in Neural Networks
por: Dopico-Castro, Alejandro, et al.
Publicado: (2025)

Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Compression of Deep Neural Networks
por: Cichocki, Andrzej, et al.
Publicado: (2026)

Complexity Horizons of Compressed Models in Analog Circuit Analysis
por: Mbonimpa, Pacome Simon
Publicado: (2026)

The Role of Quantum in Hybrid Quantum-Classical Neural Networks: A Realistic Assessment
por: Freinberger, Dominik, et al.
Publicado: (2026)

Optimizing Deep Neural Networks using Safety-Guided Self Compression
por: Zbeeb, Mohammad, et al.
Publicado: (2025)

Compression Repair for Feedforward Neural Networks Based on Model Equivalence Evaluation
por: Mo, Zihao, et al.
Publicado: (2024)

Frequency Composition for Compressed and Domain-Adaptive Neural Networks
por: Kwon, Yoojin, et al.
Publicado: (2025)

Energy Consumption in Parallel Neural Network Training
por: Huber, Philipp, et al.
Publicado: (2025)

On the Impact of Class Imbalance on the Learning Dynamics of Deep Neural Networks:An Intuitive Insight
por: Mustapha, Ismail B., et al.
Publicado: (2026)

Advancing On-Device Neural Network Training with TinyPropv2: Dynamic, Sparse, and Efficient Backpropagation
por: Rüb, Marcus, et al.
Publicado: (2024)

DREAM: Domain-aware Reasoning for Efficient Autonomous Underwater Monitoring
por: Wu, Zhenqi, et al.
Publicado: (2025)

Monitizer: Automating Design and Evaluation of Neural Network Monitors
por: Azeem, Muqsit, et al.
Publicado: (2024)

Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Driving
por: Su, Wensheng, et al.
Publicado: (2024)