TIA Toolbox
🖥 Github: https://github.com/tissueimageanalytics/tiatoolbox
📕 Paper: https://arxiv.org/pdf/2402.09990v1.pdf
✨ Tasks: https://paperswithcode.com/task/whole-slide-images
@Machine_learn
🖥 Github: https://github.com/tissueimageanalytics/tiatoolbox
📕 Paper: https://arxiv.org/pdf/2402.09990v1.pdf
✨ Tasks: https://paperswithcode.com/task/whole-slide-images
@Machine_learn
PDD: Positional Discourse Divergence
🖥 Github: https://github.com/williamlyh/pos_div_metric
📕 Paper: https://arxiv.org/pdf/2402.10175v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/recipe1m-1
✨ Tasks: https://paperswithcode.com/task/coherence-evaluation
@Machine_learn
🖥 Github: https://github.com/williamlyh/pos_div_metric
📕 Paper: https://arxiv.org/pdf/2402.10175v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/recipe1m-1
✨ Tasks: https://paperswithcode.com/task/coherence-evaluation
@Machine_learn
👍4
Visually Dehallucinative Instruction Generation: Know What You Don't Know
🖥 Github: https://github.com/ncsoft/idk
📕 Paper: https://arxiv.org/pdf/2402.09717v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/visual-question-answering
✨ Tasks: https://paperswithcode.com/task/hallucination
@Machine_learn
🖥 Github: https://github.com/ncsoft/idk
📕 Paper: https://arxiv.org/pdf/2402.09717v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/visual-question-answering
✨ Tasks: https://paperswithcode.com/task/hallucination
@Machine_learn
👍2
با عرض سلام جايگاه دوم از اين مقاله باقي مونده دوستاني كه نياز دارن ني تونن با بنده در ارتباط باشند
@Raminmousa
@Raminmousa
❤2
Energy-Time-series-anomaly-detection
🖥 Github: https://github.com/HardikPrabhu/Energy-Time-series-anomaly-detection
📕 Paper: https://arxiv.org/pdf/2402.14384v1.pdf
✨ Tasks: https://paperswithcode.com/task/anomaly-detection
@Machine_learn
🖥 Github: https://github.com/HardikPrabhu/Energy-Time-series-anomaly-detection
📕 Paper: https://arxiv.org/pdf/2402.14384v1.pdf
✨ Tasks: https://paperswithcode.com/task/anomaly-detection
@Machine_learn
❤8
🎓 Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot.
▪Github
▪Paper
▪Dataset
@Machine_learn
▪Github
▪Paper
▪Dataset
@Machine_learn
👍6❤1
Introduction to Generative AI.pdf
12.5 MB
Book: 📚Introduction to Generative AI
Authors: Numa Dhamani and Maggie Engler
ISBN: Null
year: 2023
pages: 318
Tags: #AI
@Machine_learn
Authors: Numa Dhamani and Maggie Engler
ISBN: Null
year: 2023
pages: 318
Tags: #AI
@Machine_learn
❤7
Graph Diffusion Policy Optimization
🖥 Github: https://github.com/sail-sg/gdpo
📕 Paper: https://arxiv.org/pdf/2402.16302v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/zinc
✨ Tasks: https://paperswithcode.com/task/graph-generation
@Machine_learn
🖥 Github: https://github.com/sail-sg/gdpo
📕 Paper: https://arxiv.org/pdf/2402.16302v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/zinc
✨ Tasks: https://paperswithcode.com/task/graph-generation
@Machine_learn
👍1
DCVSMNet: Double Cost Volume Stereo Matching Network
🖥 Github: https://github.com/m2219/dcvsmnet
📕 Paper: https://arxiv.org/pdf/2402.16473v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/kitti
✨ Tasks: https://paperswithcode.com/task/stereo-matching-1
@Machine_learn
🖥 Github: https://github.com/m2219/dcvsmnet
📕 Paper: https://arxiv.org/pdf/2402.16473v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/kitti
✨ Tasks: https://paperswithcode.com/task/stereo-matching-1
@Machine_learn
👍7
Fundamentals of Data Science.pdf
12.4 MB
Book: 📚Fundamentals of Data Science Theory and Practice
Authors: Jugal K. Kalita Dhruba K. Bhattacharyya Swarup Roy
ISBN: 978-0-323-91778-0
year: 2023
pages: 336
Tags: #Data_science
@Machine_learn
Authors: Jugal K. Kalita Dhruba K. Bhattacharyya Swarup Roy
ISBN: 978-0-323-91778-0
year: 2023
pages: 336
Tags: #Data_science
@Machine_learn
🔥5❤1👍1
👍1
با عرض سلام
مقاله ي فوق به صورت كامل نوشته شده است. نيازمند شخصي هستيم كه بتونه اكسپت مقاله رو بگيره و هزينه هاي سرور رو پرداخت كنه(جايگاه ٢: co-author).
@Raminmousa
مقاله ي فوق به صورت كامل نوشته شده است. نيازمند شخصي هستيم كه بتونه اكسپت مقاله رو بگيره و هزينه هاي سرور رو پرداخت كنه(جايگاه ٢: co-author).
@Raminmousa
ZHEM: An Integrated Data Processing Framework for Pretraining Foundation Models
🖥 Github: https://github.com/emanual20/zhem
📕 Paper: https://arxiv.org/pdf/2402.16358v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/wikitext-2
@Machine_learn
🖥 Github: https://github.com/emanual20/zhem
📕 Paper: https://arxiv.org/pdf/2402.16358v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/wikitext-2
@Machine_learn
❤2👍2
🖼 Differential Diffusion: Giving Each Pixel Its Strength 🔥
▪code: github.com/exx8/differential-diffusion
▪page: differential-diffusion.github.io
▪paper: arxiv.org/abs/2306.00950
@Machine_learn
▪code: github.com/exx8/differential-diffusion
▪page: differential-diffusion.github.io
▪paper: arxiv.org/abs/2306.00950
@Machine_learn
👍4❤2🔥2
aipython.pdf
2.4 MB
Book: 📚Python code for Artificial Intelligence Foundations of Computational Agents
Authors: David L. Poole and Alan K. Mackworth
year: 2024
pages: 392
Tags: #Python
@Machine_learn
Authors: David L. Poole and Alan K. Mackworth
year: 2024
pages: 392
Tags: #Python
@Machine_learn
👍7
⚡️ ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models
▪page: https://res-adapter.github.io
▪paper: https://arxiv.org/abs/2403.02084
▪code: https://github.com/bytedance/res-adapter
@Machine_learn
▪page: https://res-adapter.github.io
▪paper: https://arxiv.org/abs/2403.02084
▪code: https://github.com/bytedance/res-adapter
@Machine_learn
🔥2