MobileNetV3
PulseAugur coverage of MobileNetV3 — every cluster mentioning MobileNetV3 across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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OrthKD framework extracts clinical knowledge for lightweight diabetic retinopathy screening
Researchers have developed OrthKD, a novel knowledge distillation framework designed to extract generalized clinical knowledge from heterogeneous AI models for lightweight deployment in diabetic retinopathy screening. T…
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Hybrid deep learning model enhances slate tile traceability and classification
Researchers have developed a hybrid deep learning model to improve the traceability and classification of industrial slate tiles. This approach combines feature matching using XFeat and LightGlue with a MobileNetV3-base…
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Hybrid deep learning model enhances slate tile traceability and classification
Researchers have developed a hybrid deep learning model to improve the traceability and classification of industrial slate tiles. This approach combines instance-aware re-identification and extraction site classificatio…
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Automated pipeline uncovers bias in MoE4 architecture search
Researchers have developed an automated pipeline to explore heterogeneous 4-Expert Mixture-of-Experts (MoE4) architectures within the LEMUR dataset ecosystem. This pipeline systematically combines base architecture fami…
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New GazeLNN model predicts human attention for robot navigation
Researchers have developed GazeLNN, a novel and computationally efficient model for predicting human visual attention in real-time. This model utilizes Liquid Neural Networks and MobileNetV3 to predict fixation heatmaps…
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New Finetuning Method Adapts DNNs for ReRAM In-Memory Computing
Researchers have developed a new finetuning method to adapt deep neural networks for deployment on ReRAM-based in-memory computing hardware. This approach addresses the challenges of I-V non-linearity and retention erro…
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Stable Diffusion used for data augmentation in indoor scene recognition
Researchers have proposed a new method for indoor scene recognition by using Stable Diffusion to generate synthetic images for data augmentation. This approach addresses the scarcity of training data for indoor environm…
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Spacecraft Perception Model Achieves Top Ranking in SPARK 2026 Challenge
Researchers have developed a novel segmentation-based detection method for multi-task spacecraft perception, addressing challenges like limited annotated data and difficult visual conditions. Their compact architecture,…
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LLMs Evaluate AI Explainability in Skin Disease Diagnosis
Researchers have developed a new framework to evaluate the explainability of AI models used for diagnosing facial skin diseases. This framework utilizes large language models (LLMs) like GPT-5.5, Gemini 3.5 Flash, and C…
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New framework evaluates AI driver models on more than just accuracy
Researchers have introduced a new framework for evaluating driver monitoring models, moving beyond simple accuracy metrics. The Human-Centered Benchmarking Framework (HCBF) assesses models on accuracy, explainability, e…
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AI distills multiplexed microscopy data for single-channel tissue segmentation
Researchers have developed a cross-modal knowledge distillation framework to improve single-channel tissue segmentation in microscopy. This method transfers knowledge from a foundation model trained on multiplexed image…