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Quantization-aware training using Tensorflow Object Detection API and compile Edge TPU model.
LiME (formerly DMD) is a Loadable Kernel Module (LKM), which allows the acquisition of volatile memory from Linux and Linux-based devices, such as those powered by Android. The tool supports acquiring memory either to the file system of the device or over the network. LiME is unique in that it is the first tool that allows full memory captures from Android devices. It also minimizes its interaction between user and kernel space processes during acquisition, which allows it to produce memory captures that are more forensically sound than those of other tools designed for Linux memory acquisition.
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
Python API and command line interface for the numer.ai machine learning competition
Repositories
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LiME (formerly DMD) is a Loadable Kernel Module (LKM), which allows the acquisition of volatile memory from Linux and Linux-based devices, such as those powered by Android. The tool supports acquiring memory either to the file system of the device or over the network. LiME is unique in that it is the first tool that allows full memory captures from Android devices. It also minimizes its interaction between user and kernel space processes during acquisition, which allows it to produce memory captures that are more forensically sound than those of other tools designed for Linux memory acquisition.
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
Python API and command line interface for the numer.ai machine learning competition
No description provided.
Sample Code for Deep Learning OSS in Google Colaboratory
Quantization-aware training using Tensorflow Object Detection API and compile Edge TPU model.
MCP server to provide Figma layout information to AI coding agents like Cursor
Table with many features for Streamlit. This component use Bootstrap and FontAwesome.
open-interpreter docker environment
ssaw12 example files
Extract video features from raw videos using multiple GPUs. We support RAFT and PWC flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, ResNet features.
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Official repo for BMVC2021 paper ASFormer: Transformer for action segmentation
Code for ''Alleviating Over-segmentation Errors by Detecting Action Boundaries'' accepted in WACV2021
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation (TPAMI 2020)
No description provided.
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Models and examples built with TensorFlow
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🛡️ ⚛️ A simple, scalable, and powerful architecture for building production ready React applications.
No description provided.
Amazon Chime React Component Library with integrations with the Amazon Chime SDK.
The official example scripts for the Numerai Data Science Tournament
This repository contains samples intended to demonstrate different use cases for the Amazon Chime SDK (JavaScript, iOS, Android, React, Messaging and Telephony)
Human Pose Detection on EdgeTPU
A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
Google Brain AutoML
PyTorch implementation of "Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection"
Motion Retargeting Video Subjects