Computational Efficiency
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Benchmarks
Plant village
Most implemented
Rethinking the Inception Architecture for Computer Vision
Attention U-Net: Learning Where to Look for the Pancreas
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies
Simple random search provides a competitive approach to reinforcement learning
Papers
A Bio-Plausible Visual Neural Network for Locust-Inspired Collision Perception
Locust visual systems have long served as an important biological paradigm for studying looming perception and collision avoidance. Numerous computational models have successfully reproduced the selective responses of Lo…
Computational EfficiencyCollision AvoidancePccDiffuser: Multi-solution Motion Planning for Continuum Robots
We present the PccDiffuser, a conditional diffusion framework for continuum robots that learns a multimodal distribution over complete configuration-space paths and samples multiple candidate solutions in parallel, which…
Computational EfficiencyGraph Neural NetworkMotion PlanningCan Artificial Intelligence Support Healthcare and Mental Health Through Early Cyberbullying Detection ? The Impact of Emotion-Aware AI on Proactive Online Safety
Healthcare systems, mental health, and public well-being are increasingly affected by cyberbullying and harmful online interactions. This paper presents CareGuard, an early-warning framework designed to support healthcar…
Computational EfficiencyReactVAU: A Slow-Fast Decoupled Framework for Streaming Video Anomaly Understanding
In this paper, we propose ReactVAU, a Slow-Fast Decoupled Framework for real-time streaming Video Anomaly Understanding (VAU). Existing VAU methods rely on offline inference with global temporal sampling, which violates …
Computational EfficiencyAnomaly DetectionAdaptive Gated Deepfake Detection for Low-Resolution and Resource-Constrained Environments
Deepfake detection models often rely on high-quality inputs, fixed inference paths, and computationally expensive architectures, limiting their use in low-resolution and resource-constrained settings. This paper proposes…
Computational EfficiencyDeepFake DetectionVLA-Precision: Asymmetric Co-Bootstrapping for Efficient Real-World Online RL of Vision-Language-Action Models
Pretrained vision-language-action (VLA) models enable broad manipulation but remain unreliable in tasks demanding precision and repeatability. Applying real-world online reinforcement learning (RL) to VLA post-training e…
Computational EfficiencyReinforcement Learning