deep-learning
LEVIR-CDarxiv_deep_learning_python_research_code_functions_summaries
Dataset Card for "AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries"
Dataset Description
https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries
Dataset Summary
AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries contains summaries for every python function and class extracted from source code files referenced in ArXiv papers. The… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code_functions_summaries.DeepLearningProject
Deep Learning Project
Dataset Summary
This repository contains the datasets, trained models, notebooks, experiments, feature-extraction outputs, and supporting resources developed for a deep learning project focused on fire detection, fire severity classification, and related computer vision tasks.
The project covers multiple stages of a deep learning workflow, including binary fire classification, three-class fire severity classification, feature extraction… See the full description on the dataset page: https://huggingface.co/datasets/AbdullahImran/DeepLearningProject.AutoStitch
AutoStitch Studio
AI-Powered Video Composition Tool for Windows
A locally-run, offline-first Windows desktop application that automates voiceover generation, sound effect creation, and multi-lane video stitching — all without any cloud dependency.
No cloud. No subscriptions. Everything runs on your machine.
What It Does
AutoStitch Studio gives content creators a 3-lane timeline to compose videos:
Lane
Input
Engine
Video
Folder of .mp4… See the full description on the dataset page: https://huggingface.co/datasets/deepLEARNING786/AutoStitch.VHR-10The VHR-10 dataset mirrored from https://github.com/chaozhong2010/VHR-10_dataset_coco
NWPU VHR-10 data set is a challenging ten-class geospatial object detection data set. This dataset contains a total of 800 VHR optical remote sensing images, where 715 color images were acquired from Google Earth with the spatial resolution ranging from 0.5 to 2 m, and 85 pansharpened color infrared images were acquired from Vaihingen data with a spatial resolution of 0.08 m. The data set is divided into two… See the full description on the dataset page: https://huggingface.co/datasets/satellite-image-deep-learning/VHR-10.SODA-ASODA-A comprises 2513 high-resolution images of aerial scenes, which has 872069 instances annotated with oriented rectangle box annotations over 9 classes.
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