SPIN Unprocessed October 23, 2026 ai_technology research
GANet: A Lightweight Group Attention Network for Plant Disease Identification on Embedded Systems
View original on arxiv.orgOverview
arXiv:2610.30225v1 Announce Type: new Abstract: Global warming and climate change are major catalysts for plant diseases, significantly affecting food production worldwide. Addressing this issue requires continuous monitoring and early detection of plant diseases. While recent advancements in deep learning offer potential solutions, most models demand high processing power and struggle to perform efficiently on low-end electronic hardware. Furthermore, many existing works focus on specific crop
SpinGraph analysis pending — check back after processing.
Ask AI about this story
Opens with the SpinGraph .md URL and structured context — one click, prompt included.
More from arXiv Machine Learning
View all →- AcoustiPrint: Physics-Guided Neural Design of Manufacturable Acoustic Structures
- Escaping the Phylogenetic Trap: Persistent Homology Enables Cross-Species Ion Channel Classification via Multimodal Graph Neural Networks
- Bayesian Fixed-Confidence Best-Arm Identification with Abstention
- Probing and Steering for Safety-Relevant Behaviours in Large Language Models
- CTRL-FM: Inference-Time Structural Control for Flow-Based Virtual Sensing under Long-Horizon Node Outages
- Spike-Aware Gradient-Based Mixed-Precision Quantization of Spiking Neural Networks for Vision Applications
Markdown (.md) · JSON-LD schema (.json) · Machine-readable for AI & GEO