ZMIS-SAM: Segment Anything Model Enhanced with Wavelet Transform for Zooplankton Microscopy Image Instance Segmentation

arXiv:2607.27585 · cs.CV · Submitted 2026-07-30 · Read on arXiv

cs.CV

Submitted: 2026-07-30

Updated: 2026-09-21

Terminology

• Instance Segmentation — 78× in this paper · explained in 3 episodes
• Wavelet Transform — 21× in this paper · explained in 2 episodes
• Generalization — 12× in this paper · explained in 13 episodes
• Segment Anything Model — 12× in this paper
• Accuracy — 11× in this paper · explained in 1 episode
• Transformer — 11× in this paper · explained in 2 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 9× in this paper
• Aggregation — 7× in this paper · explained in 1 episode
• Neighboring Feature Aggregation Module — 7× in this paper
• Shape Adapter — 7× in this paper
• Intensity Adapter — 6× in this paper
• Loss Function — 6× in this paper · explained in 2 episodes
• Segment Anything Model (SAM) — 5× in this paper · explained in 2 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Attention Mechanism — 3× in this paper · explained in 3 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Downstream Tasks — 3× in this paper · explained in 2 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• alpha — 3× in this paper · explained in 1 episode
• Activation Function — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• IEEE International Conference on Computer Vision — 2× in this paper
• Layer Normalization — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Average Precision — 1× in this paper
• Clustering — 1× in this paper · explained in 2 episodes
• Computer Analysis of Images and Patterns — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• International Conference on Machine Learning — 1× in this paper
• Parameter-Efficient Fine-Tuning — 1× in this paper · explained in 2 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes

Sources

• Bottom-up Instance Segmentation using Deep Higher-Order CRFs
• Any-to-Any Style Transfer: Making Picasso and Da Vinci Collaborate
• SAM 2: Segment Anything in Images and Videos
• Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
• Inpaint Anything: Segment Anything Meets Image Inpainting
• A Comprehensive Survey on Segment Anything Model for Vision and Beyond

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