CNN visualization tool in TensorFlow
- tensorflow
- tensorboard
- convolutional-neural-networks
- cnn
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CNN visualization tool in TensorFlow
Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.
AI drew your research figure. Tavotto makes it publication-ready: edit matplotlib and AI-generated figures on a canvas, lay out multi-panel pages in mm, check journal rules before export. Scripts stay untouched.
A Python package to visualise neuroanatomical data in atlas space
Interactive network visualization in Python and Dash, powered by Cytoscape.js
An elegant Python interface for visualization on the web platform to interactively generate insights into multidimensional images, point sets, and geometry.
Spatial Single Cell Analysis in Python
Main yt repository
Keep Whale-chan consistently vivid in every generation: High-consistency character design specification, visual asset library, and agent creation suite.
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
3-D Scientific Visualization in the Jupyter Notebook
Visualization Package for NetworkX
[Reimplementation Antol et al 2015] Keras-based LSTM/CNN models for Visual Question Answering
Official Code for OpenVLHarness: Real-World Visual Agentic Tool‑Use with Multimodal Memory
Real-time generative rendering for interactive worlds, from any visual reference.
A 4B grounding foundation model for physical intelligence. Unifies detection, referring, pointing, OCR, GUI, and layout grounding, achieving SOTA overall across 34 benchmarks and improving robot generalization and data efficiency in controlled evaluations.
Reconquer the canvas: beautiful Tikz figures without clunky Tikz code
A python package for animating plots build on matplotlib.
Open-source AI navigation glasses under $35 — they say what they see, and say 'uncertain' instead of guessing. Safety-first, printable enclosure, community build kit.
🎆 A visualization of the CapsNet layers to better understand how it works
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
Visualize network topologies and collect graph statistics based on pcap files
Micropython Project Management Tool with VSCode support, Linting, Intellisense, Dependency Management, and more!
FlexGlue: Sparse-to-Dense Feature Matching and Visual Disambiguation