TensorFlow Lite
PulseAugur coverage of TensorFlow Lite — every cluster mentioning TensorFlow Lite across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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PrintGuard 2.0 launches with 5MB TFLite model for browser and CPython
PrintGuard 2.0 is an updated system for detecting failures in 3D printing, utilizing a ShuffleNetV2 encoder and a prototypical network for few-shot fault detection. The new version features a significantly smaller Tenso…
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AI mobile guide for Grand Egyptian Museum developed
Researchers have developed TimeLens, an AI-powered mobile guide for the Grand Egyptian Museum. This system can recognize artifacts in real-time and answer visitor questions in English or Arabic. The project involved cre…
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Tiny collaborative inference boosts object detection on edge devices
Researchers have developed a method for improving object detection on small edge devices, particularly in scenarios with occlusion. Their approach combines a lightweight neural network architecture with TensorFlow Lite …
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DCGAN runs on RISC-V microcontroller with 512KB SRAM
A project successfully implemented a 12.6 million parameter DCGAN model for generating 64x64 cat faces on a dual-core RISC-V microcontroller with only 512KB of SRAM. The inference engine, written entirely in C, achieved…
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Deep learning ensemble boosts plant disease classification accuracy
Researchers have developed AgriMind, an ensemble deep learning framework designed to automate plant disease classification. This system combines three models—ResNet50, EfficientNet-B0, and DenseNet121—trained on over 20…
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AI model grades knee osteoarthritis severity on limited devices
Researchers have developed a novel approach for grading knee osteoarthritis severity using a combination of deep learning and a large language model. The system utilizes a ResNet-18 convolutional neural network, optimiz…
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PoTAcc pipeline accelerates power-of-two quantized DNNs on edge devices
Researchers have developed PoTAcc, an open-source pipeline designed to accelerate the deployment of power-of-two (PoT) quantized deep neural networks (DNNs) on resource-constrained edge devices. This system facilitates …
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AI models advance plant disease detection with new datasets and efficient distillation
Researchers have developed new methods for plant leaf disease classification to aid in early detection and treatment. One approach involves training a new base model using the DenseNet201 architecture on a custom datase…
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AI model predicts stuttering events from audio, deploys on-device
Researchers have developed a new Convolutional Neural Network (CNN) model capable of predicting upcoming stuttering events from short audio clips. The 616K-parameter model, trained on the SEP-28k dataset, demonstrates a…