Adnan Saeed

Adnan Saeed is a deep learning researcher working on medical image analysis, with a focus on multimodal architectures, graph neural networks, and evidential deep learning for clinical imaging tasks. His peer reviewed research has appeared in journals across machine learning and biomedical signal processing. At AI Trend Blend he turns recent papers into clear, practical explainers, with an emphasis on what a method actually does and where it holds up, written for readers who want depth without the hype.

10 Best Gemini Pro 3.1 Prompts.

10 Best Gemini Pro 3.1 Prompts to Automate Full-Stack Development in 2026

Leave a Comment / Google Gemini, Prompt Engineering /

10 Best Gemini Pro 3.1 Prompts to Automate Full-Stack Development in 2026 AITrendBlend PROMPT ENGINEERING · GEMINI 2026 Gemini Pro 3.1 · Full-Stack Development · 2026 Guide 10 Gemini Pro 3.1 Prompts to Automate Full-Stack Development in 2026 From spinning up a project scaffold in seconds to auto-generating APIs, tests, and deployment configs. These are […]

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Fusion-Mamba: Hidden State Space Fusion for Cross-Modality Object Detection

Fusion-Mamba: Hidden State Space Fusion for Cross-Modality Object Detection

Leave a Comment / Machine Learning, Computer Vision, Multimodal AI, Vision Transformers & Attention /

Fusion-Mamba: Hidden State Space Fusion for Cross-Modality Object Detection | AI Trend Blend AITrendBlend Machine Learning Computer Vision About Computer Vision · arXiv:2404.09146 · Beihang University · 21 min read Mamba Goes Multimodal: How Fusion-Mamba Built a Hidden State Space to End Modality Disparity Researchers at Beihang University asked what happens when you stop treating

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IRDFusion: Iterative Differential Feedback for Multispectral Object Detection.

IRDFusion: Iterative Differential Feedback for Multispectral Object Detection

Leave a Comment / Machine Learning, Computer Vision, Multimodal AI, Remote Sensing AI /

IRDFusion: Iterative Differential Feedback for Multispectral Object Detection | AI Trend Blend AITrendBlend Machine Learning Computer Vision About Computer Vision · arXiv:2509.09085 · Jiangsu University · 20 min read The Feedback Loop That Fixes Multispectral Detection: How IRDFusion Borrowed from Circuit Design to Beat the State of the Art Researchers at Jiangsu University asked a

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10 Best ChatGPT Plus Prompts for Social Media Content.

10 Best ChatGPT Plus Prompts for Social Media Content Creation (2026 Guide)

Leave a Comment / Prompt Engineering, ChatGPT /

10 Best ChatGPT Plus Prompts for Social Media Content Creation (2026 Guide) aitrendblend Prompt Engineering Machine Learning About Prompt Engineering · ChatGPT Plus · Social Media 10 Best ChatGPT Plus Prompts for Social Media Content Creation From daily captions to full brand strategy — prompts tested in 2026, escalating from beginner to master, with honest

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SLGNet: Structural Priors and Language-Guided Modulation for Multimodal Object Detection.

SLGNet: Structural Priors and Language-Guided Modulation for Multimodal Object Detection

Leave a Comment / Machine Learning, Computer Vision, Multimodal AI /

SLGNet: Structural Priors and Language-Guided Modulation for Multimodal Object Detection | AI Trend Blend AITrendBlend Machine Learning Computer Vision About Computer Vision · arXiv:2601.02249 · January 2026 · 22 min read When the Camera Goes Blind: How SLGNet Uses Language and Structure to See in the Dark Researchers at the Chinese Academy of Sciences built

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HMHI-Net: Hierarchical Memory with Heterogeneous Interaction for Video Object Segmentation.

HMHI-Net: Hierarchical Memory with Heterogeneous Interaction for Video Object Segmentation

Leave a Comment / Machine Learning, Computer Vision /

HMHI-Net: Hierarchical Memory with Heterogeneous Interaction for Video Object Segmentation | AI Trend Blend AITrendBlend Machine Learning Computer Vision About Computer Vision · ACM Multimedia 2025 · arXiv:2507.22465 · 20 min read Shallow Features Matter: How HMHI-Net Fixes the Fundamental Flaw in Video Object Segmentation Memory Fudan University researchers discovered that every existing memory-based video

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FedLSC: Federated Learning with Layer Similarity Comparison for Skin Cancer.

FedLSC: Federated Learning with Layer Similarity Comparison for Skin Cancer

Leave a Comment / Machine Learning, Computer Vision, Federated Learning & AI Privacy, Medical AI /

FedLSC: Federated Learning with Layer Similarity Comparison for Skin Cancer | AI Trend Blend AITrendBlend Machine Learning Computer Vision Medical AI About Federated Learning · Expert Systems With Applications 306 (2026) 130937 · 22 min read FedLSC: The Smarter Way to Train a Skin Cancer AI Across Hospitals Without Sharing Any Patient Data Researchers at

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Class-Weighted DQN for Skin Cancer Classification.

Class-Weighted DQN for Skin Cancer Classification

Leave a Comment / Machine Learning, Computer Vision, Medical AI /

Class-Weighted DQN for Skin Cancer Classification | AI Trend Blend AITrendBlend Machine Learning Computer Vision Medical AI About Medical AI · Expert Systems With Applications 293 (2025) 128426 · 18 min read Teaching an AI to Care More About the Rarest Cancers: Class-Weighted DQN for Skin Cancer Classification Researchers from KTO Karatay University and Selcuk

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BGPANet: How Bi-Granular Progressive Attention Cracked the Skin Cancer Diagnosis Problem

BGPANet: How Bi-Granular Progressive Attention Cracked the Skin Cancer Diagnosis Problem

Leave a Comment / Machine Learning, Computer Vision, Medical AI, Vision Transformers & Attention /

BGPANet: How Bi-Granular Progressive Attention Cracked the Skin Cancer Diagnosis Problem | AI Medical Research AIMedical Research Machine Learning Medical AI About Medical Image AI · Expert Systems With Applications 321 (2026) 132169 · 16 min read BGPANet: The Bi-Granular Attention Breakthrough That Finally Taught AI to Diagnose Skin Cancer Like a Dermatologist How a

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