Seeing Clearly: AI Sharpens Focus on Real-Time Surgical Scene Understanding
![The research details a surgical video analysis pipeline-SpikeSurgSeg-which leverages a pretrained, spike-driven video encoder employing layer-wise tube masking for reconstruction, and integrates this with a spike-driven memory readout and feature pyramid network, ultimately achieving surgical scene segmentation with an SNN-based model distinguished by its two spike-driven CNN blocks and two spike-driven spatiotemporal Transformers exhibiting linear space-time computational complexity-[latex]O(N)[/latex].](https://arxiv.org/html/2512.21284v1/x2.png)
A new framework leverages spiking neural networks and video transformers to deliver accurate and energy-efficient segmentation of surgical video feeds.
Science
Smarter IoT Security: Classifying Encrypted Traffic with AI
![A diffusion-based system extracts multi-level features from traffic imagery by progressively introducing noise, then leveraging a U-Net architecture to denoise and identify optimal feature layers-a process refined through [latex]K[/latex]-means clustering for efficient fine-tuning-and ultimately fusing adjacent network layer features to represent both detailed and abstract traffic patterns.](https://arxiv.org/html/2512.21144v1/x2.png)
A new approach leverages the power of diffusion models and large language models to accurately identify network traffic even within the limitations of resource-constrained IoT devices.
Lightning Network’s Tightrope Walk: Stability and Centralization
A new analysis reveals the Lightning Network maintains surprising resilience over time, even as it becomes increasingly fragmented and concentrated in its structure.
Steering with Intelligence: Magnetic Catheters Guided by AI
![A reinforcement learning system leverages an LSTM-modeled magnetic catheter-where state is defined by tip position [latex]X_{t},Y_{t}[/latex] and goal [latex]X_{g},Y_{g}[/latex]-to train an agent, employing either a Deep Q-Network or TD3, to select angular increments [latex]\Delta\theta_{1},\,\Delta\theta_{3}[/latex]-with [latex]\Delta\theta_{2}=\Delta\theta_{1}[/latex] due to coupling-and optimize a reward function balancing goal proximity with control effort, effectively establishing closed-loop control of the catheter’s tip.](https://arxiv.org/html/2512.21063v1/Overview2.png)
Researchers are leveraging the power of artificial intelligence to achieve unprecedented precision in navigating magnetically steered catheters within the body.
Digital Distress Signals: Tracking Mental Health on Reddit During COVID-19
A new analysis of online forum data reveals shifting trends in mental wellbeing throughout the pandemic, offering a unique window into population-level emotional states.
Forecasting the Skies: A New Approach to Predicting Rainfall
Researchers have developed a novel deep learning model that significantly improves the accuracy and realism of short-term precipitation forecasts.
Can AI Decode the Signals of Mental Health?
A new benchmark framework assesses the ability of foundation models to detect neuropsychiatric disorders from speech and text, revealing both promise and significant challenges.
Seeing Beyond Blockages: A New View of Heart Vessel Health
Researchers are leveraging advanced image analysis to better understand and diagnose subtle problems in the smallest blood vessels of the heart.
Guarding AI Perception: A New Defense Against Activity Recognition Hacks
Researchers have developed an autonomous agent that actively shields AI systems interpreting sensor data from malicious prompt injection attacks.
Smart Networks for Industry 4.0: Scaling Intent-Based Control with Federated Learning
A new framework harnesses the power of distributed AI to verify network policies and optimize performance in complex Industrial IoT deployments.