nqt228's Stars
nqt228/YoloZ
microsoft/T-MAC
Low-bit LLM inference on CPU with lookup table
abetlen/llama-cpp-python
Python bindings for llama.cpp
mlabonne/llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
ollama/ollama
Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
DepthAnything/Depth-Anything-V2
Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation
alibaba-yuanjing-aigclab/ViViD
ViViD: Video Virtual Try-on using Diffusion Models
cvat-ai/cvat
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
wangchen1801/FPD
Official code of the paper "Fine-Grained Prototypes Distillation for Few-Shot Object Detection (AAAI 2024)"
ucbdrive/few-shot-object-detection
Implementations of few-shot object detection benchmarks
ThanhPham1987/CV-try-on-StableVITON
[CVPR2024] StableVITON: Learning Semantic Correspondence with Latent Diffusion Model for Virtual Try-On
geyuying/PF-AFN
Official code for "Parser-Free Virtual Try-on via Distilling Appearance Flows", CVPR 2021.
ThanhPham1987/ChebyKAN
Kolmogorov-Arnold Networks (KAN) using Chebyshev polynomials instead of B-splines.
vanhaotruong/Similarity_Search
Searching similar images
aleksada/DeepKriging
PointCloudYC/Deep-Learning-On-Point-Clouds
A curated list of primary sources on applying deep learning on point cloud data.
qyz96/DeepBayesian
doans/Underwater-Acoustic-Target-Classification-Based-on-Dense-Convolutional-Neural-Network
In oceanic remote sensing operations, underwater acoustic target recognition is always a difficult and extremely important task of sonar systems, especially in the condition of complex sound wave propagation characteristics. Expensively learning recognition model for big data analysis is typically an obstacle for most traditional machine learning (ML) algorithms, whereas convolutional neural network (CNN), a type of deep neural network, can automatically extract features for accurate classification. In this study, we propose an approach using a dense CNN model for underwater target recognition. The network architecture is designed to cleverly re-use all former feature maps to optimize classification rate under various impaired conditions while satisfying low computational cost. In addition, instead of using time-frequency spectrogram images, the proposed scheme allows directly utilizing original audio signal in time domain as the network input data. Based on the experimental results evaluated on the real-world dataset of passive sonar, our classification model achieves the overall accuracy of 98.85$\%$ at 0 dB signal-to-noise ratio (SNR) and outperforms traditional ML techniques, as well as other state-of-the-art CNN models.
xinzhichao/Underwater_Datasets
This repository is used to collect underwater scene datasets and is always updated
tloen/alpaca-lora
Instruct-tune LLaMA on consumer hardware
WongKinYiu/yolov9
Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
google/gemma.cpp
lightweight, standalone C++ inference engine for Google's Gemma models.
natowi/3D-Reconstruction-with-Deep-Learning-Methods
List of projects for 3d reconstruction
Flowx08/artificial_intelligence
My C++ deep learning framework & other machine learning algorithms
Utkarsh-Deshmukh/Single-Image-Dehazing-Python
python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"
ThanhPham1987/text-generation-webui
A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
ThanhPham1987/the-algorithm
Source code for Twitter's Recommendation Algorithm
ThanhPham1987/rags
Build ChatGPT over your data, all with natural language
ThanhPham1987/TotalSegmentator
Tool for robust segmentation of >100 important anatomical structures in CT images
ThanhPham1987/chessai
Chinese Chess Advanced Analytics